Artykuły w czasopismach na temat „Design problem solutions”
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MA, Henry, i Amelie CHAN. "Demystification of Design Thinking in Problem-solving". 11th GLOBAL CONFERENCE ON BUSINESS AND SOCIAL SCIENCES 11, nr 1 (9.12.2020): 141. http://dx.doi.org/10.35609/gcbssproceeding.2020.11(141).
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As one of the key components in design discipline, Design Thinking has regained its popularity in the last decade (Dunne & Martin, 2006; Cooper, Junginger & Lockwood, 2009; Kimbell, 2011). However, this did not occur in design schools or in design professions; rather, it occurred in other disciplines—like business. Some business schools and business organizations consider Design Thinking an effective method or process to generate innovative solutions for resolving complex or wicked problems (Davis, 2010; Dorst, 2011; Glen, Suciu & Baughn, 2014). Whether they be for-profit or non-profit, many organizations also use the Design Thinking process when making strategic decisions or solving problems. In order to solve a problem in an efficient and effective manner, traditional thinking and cognitive studies suggest the prevailing way to solve a problem is to follow an orderly and linear process that work from the problem to the solution. The logic starts by understanding the problem through analyzing the problem situation. After identifying the definition of the problem, one can formulates some possible solutions. The optional solutions are evaluated and the best will be chosen to implement and transform the situation to the specific goal. Keywords: Design Thinking, Traditional Problem-solving, Creativity, Wicked Problems
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Studer, Jaryn A., Shanna R. Daly, Seda McKilligan i Colleen M. Seifert. "Evidence of problem exploration in creative designs". Artificial Intelligence for Engineering Design, Analysis and Manufacturing 32, nr 4 (5.10.2018): 415–30. http://dx.doi.org/10.1017/s0890060418000124.
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AbstractDesign problems are often presented as structured briefs with detailed constraints and requirements, suggesting a fixed definition. However, past studies have identified the importance of exploring design problems for creative design outcomes. Previous protocol studies of designers has shown that problems can “co-evolve” with the development of solutions during the design process. But to date, little evidence has been provided abouthowdesigners systematically explore presented problems to create better solutions. In this study, we conducted a qualitative analysis of 252 design problems collected from publically available sources, including award-winning product designs and open-source design competitions. This database offers an independent sample of presented problems, designers’ alternative problem descriptions, and innovative solutions. We report the results of this large-scale qualitative analysis aimed at characterizing changes to problems during the design process. Inductive coding was used to identify content patterns in “discovered” problem descriptions, with qualitative codes reliably scored by two independent coders. A total of 32 distinct patterns of problem exploration were identified across designers and presented problems. Each pattern is described in the form of a generalized strategy to guide designers as they explore problem spaces. The exploration patterns identified in this study are the first empirical evidence of problem exploration in independent design problems. Further, the presence of exploration patterns in discovered problems is associated with the selection of the corresponding solution as a challenge finalist. These empirically identified strategies for problem exploration may be useful for computational tools supporting designers.
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Su, Ching Long, i Yann Yean Su. "Design an Optimizing Cooperative Particle Swarm Application". Advanced Materials Research 211-212 (luty 2011): 1129–32. http://dx.doi.org/10.4028/www.scientific.net/amr.211-212.1129.
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study seeks to solve the optimization problem of different engineering designs by using nonlinear mixed integer programming mode. In the past, this type of engineering design optimization problem has been widely studied and discussed. They are usually solved through mathematical programming method or heuristics. However, there are more constraints and more constraints that cannot be satisfied. In solving this type of problems, we used a penalty guided cooperative particle swarm optimization to avoid the disadvantage of decreased efficiency from the increase of search spatial dimension and to raise the efficiency. In resolving the problems of five engineering design problems, including system reliability design and machine parts design problem, the data from the study indicate that the solutions from cooperative particle swarm optimization are equal or better than the best-known solutions from past literature. Thus, the results of this study show that cooperative particle swarm optimization is another effective method to find solutions to optimization problems.
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Maher, Mary Lou. "Evolving a design focus in response to design solutions". Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10, nr 2 (kwiecień 1996): 161–62. http://dx.doi.org/10.1017/s0890060400001451.
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Most computer-based design tools assume designers work with a well-defined problem. The traditional treatment of design as two discrete phases; problem formulation and solution synthesis, is challenged by recent research. Though the view on discrete phases may be applicable to simple and/or well-defined design tasks, current research (Jonas, 1993; Logan & Smithers, 1993; Gero, 1994; Smithers et al., 1994) has shown that design is an ill-structured problem and the discrete phases view is not a good description of the process during which design alternatives are generated. A potential role of machine learning techniques is to provide a computational model of the changing representation of the design problem in response to the search for design solutions.
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Casakin, Hernan. "Factors of Design Problem-Solving and Their Contribution to Creativity". Open House International 33, nr 1 (1.03.2008): 46–60. http://dx.doi.org/10.1108/ohi-01-2008-b0005.
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Design problems are unique, complex, and ambiguous. They are considered to be non-routine and ill-structured. Since these kinds of problems require the production of innovative solutions, design problem-solving involves creative thinking. Creativity is concerned with the capacity to restructure old ideas to produce novel solutions, and the ability to search for unusual design alternatives that transcend the known and familiar. In the recent years, there were attempts to gain insight in problem-solving activities that demand creativity, such as design. A question addressed in the current empirical research is how design students assess creativity in architectural design while solving housing problems. Redefining the role of housing in the contemporary city was a main concern. Major factors of design problem-solving, and their contribution to creativity are analyzed. Results revealed that restructuring of housing design problems was the most significant factor of design problem-solving, followed by search of design solutions. Retrieval of prior knowledge from memory was the weakest factor. Furthermore, innovation was the most significant factor characterizing design creativity, followed by utility and aesthetics. Additional findings showed that restructuring of housing problems was the most correlated factor, and the predictor that had a unique contribution to all creativity factors. Search of housing solutions was a predictor that contributed mainly to innovation.
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Bonneau, Mathieu, Régis Sabbadin, Fred A. Johnson i Bradley Stith. "Dynamic minimum set problem for reserve design: Heuristic solutions for large problems". PLOS ONE 13, nr 3 (15.03.2018): e0193093. http://dx.doi.org/10.1371/journal.pone.0193093.
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Jaroslav Janáček, Michal Koháni, Dobroslav Grygar i René Fabricius. "Two Objective Public Service System Design Problem". Communications - Scientific letters of the University of Zilina 23, nr 4 (1.10.2021): E68—E75. http://dx.doi.org/10.26552/com.c.2021.4.e68-e75.
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The public service system serves population spread over a geographical area from a given number of service centers. One of the possible approaches to the problem with two or more simultaneously applied contradicting objectives is determination of the so-called Pareto front, i.e. set of all the feasible non-dominated solutions. The Pareto front determination represents a crucial computational deal, when a large public service system is designed using an exact method. This process complexity evoked an idea to use an evolutionary metaheuristic, which can build up a set of non-dominated solution continuously in the form of an elite set. Nevertheless, the latter approach does not assure that the resulting set of solutions represents the true Pareto front of the multi-objective problem solutions. Within this paper, authors deal with both approaches to evaluate the difference between the exact and heuristic approaches.
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De Keijzer, B., T. B. Klos i Y. Zhang. "Finding Optimal Solutions for Voting Game Design Problems". Journal of Artificial Intelligence Research 50 (22.05.2014): 105–40. http://dx.doi.org/10.1613/jair.4109.
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In many circumstances where multiple agents need to make a joint decision, voting is used to aggregate the agents' preferences. Each agent's vote carries a weight, and if the sum of the weights of the agents in favor of some outcome is larger than or equal to a given quota, then this outcome is decided upon. The distribution of weights leads to a certain distribution of power. Several `power indices' have been proposed to measure such power. In the so-called inverse problem, we are given a target distribution of power, and are asked to come up with a game in the form of a quota, plus an assignment of weights to the players whose power distribution is as close as possible to the target distribution (according to some specied distance measure). Here we study solution approaches for the larger class of voting game design (VGD) problems, one of which is the inverse problem. In the general VGD problem, the goal is to find a voting game (with a given number of players) that optimizes some function over these games. In the inverse problem, for example, we look for a weighted voting game that minimizes the distance between the distribution of power among the players and a given target distribution of power (according to a given distance measure). Our goal is to find algorithms that solve voting game design problems exactly, and we approach this goal by enumerating all games in the class of games of interest. We first present a doubly exponential algorithm for enumerating the set of simple games. We then improve on this algorithm for the class of weighted voting games and obtain a quadratic exponential (i.e., 2^O(n^2)) algorithm for enumerating them. We show that this improved algorithm runs in output-polynomial time, making it the fastest possible enumeration algorithm up to a polynomial factor. Finally, we propose an exact anytime-algorithm that runs in exponential time for the power index weighted voting game design problem (the `inverse problem'). We implement this algorithm to find a weighted voting game with a normalized Banzhaf power distribution closest to a target power index, and perform experiments to obtain some insights about the set of weighted voting games. We remark that our algorithm is applicable to optimizing any exponential-time computable function, the distance of the normalized Banzhaf index to a target power index is merely taken as an example.
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Bariani, Giovanni M., Rafael Lopes Ribeiro, Leonardo de Morais Soares i Artur Katz. "Creating solutions through design thinking." Journal of Global Oncology 5, suppl (7.10.2019): 20. http://dx.doi.org/10.1200/jgo.2019.5.suppl.20.
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20 Background: In recent years the impact of technology has marked a major transformation in the way society produces and generates services. Several initiatives have been developed in the health area to face this new reality. A major oncology center in Brazil carried out a project based on Design Thinking with the objective of understanding the current scenario and promoting innovative solutions for the care of cancer patients. Methods: Design Thinking is the set of ideas and insights to address problems related to information acquisition, knowledge analysis and proposal of solutions. This process took place in four stages designated as empathise (approach to the context of the problem and data collection), define (synthesis of collected information, and organization of insights in order to standardize and better understand the problem), ideate (stimulation of creativity and generation of solutions) and prototype (validation of the ideas). Results: A total of 130 interviews were carried out with hospital personnel and 46 with patients and caregivers, as well as workshops to develop the project activities. Twenty-six projects were generated, and the priorities differed according to personnel and patients. Among the projects are financial consultancy; predictability of the total cost of treatment; diversification of payment methods; customization of the food menu offered to patients; promotion of entertainment activities during waiting periods in the practice; increase interactivity of chemotherapy rooms; improvement of services offered to international patients; and development of digital tools that provide reliable information about cancer, promotes patient autonomy and strengthens patient’s relationship with the hospital personnel. Conclusions: There is a growing need to modernize oncology practices creating new products and services. The opinion of hospital personnel and patients diverged about priorities. The former have chosen projects to improve facilities and design new roles for the team while the latter have given their best evaluations to new systems and services. For patients using digital media is not only welcome but also necessary attributes to provide more information and increase their autonomy.
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Beernaert, Torben, Pascal Etman, Maarten De Bock, Ivo Classen i Marco De Baar. "TRACING THE EMERGENCE OF DESIGN PROBLEMS AND THEIR IMPACTS ON THE COMPLEXITY OF ENGINEERING SOLUTIONS". Proceedings of the Design Society 1 (27.07.2021): 3229–38. http://dx.doi.org/10.1017/pds.2021.584.
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AbstractThe design of ITER, a large-scale nuclear fusion reactor, is intertwined with profound research and development efforts. Tough problems call for novel solutions, but the low maturity of those solutions can lead to unexpected problems. If designers keep solving such emergent problems in iterative design cycles, the complexity of the resulting design is bound to increase. Instead, we want to show designers the sources of emergent design problems, so they may be dealt with more effectively. We propose to model the interplay between multiple problems and solutions in a problem network. Each problem and solution is then connected to a dynamically changing engineering model, a graph of physical components. By analysing the problem network and the engineering model, we can (1) derive which problem has emerged from which solution and (2) compute the contribution of each design effort to the complexity of the evolving engineering model. The method is demonstrated for a sequence of problems and solutions that characterized the early design stage of an optical subsystem of ITER.
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Stoustrup, Jakob, i Hans Henrik Niemann. "State-space solutions to the ℋ∞/LTR design problem". International Journal of Robust and Nonlinear Control 3, nr 1 (1993): 1–45. http://dx.doi.org/10.1002/rnc.4590030102.
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REICHELT, DIRK, i FRANZ ROTHLAUF. "RELIABLE COMMUNICATION NETWORK DESIGN WITH EVOLUTIONARY ALGORITHMS". International Journal of Computational Intelligence and Applications 05, nr 02 (czerwiec 2005): 251–66. http://dx.doi.org/10.1142/s146902680500160x.
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For the reliable communication network design (RCND) problem unreliable links are available, each bearing several options which have different levels of reliability and varying costs. The goal is to find the most cost-effective communication network design that satisfies a predefined overall reliability constraint. This paper presents two new evolutionary algorithm (EA) approaches to solving the RCND problem: LaBORNet and BaBORNet. LaBORNet uses an encoding that represents the network topology as well as the used link options while repairing infeasible solutions using an additional repair heuristic (CURE). BaBORNet encodes only the network topology and determines the link options by using the repair heuristic CURE as a local search method. The experimental results show that the new EA approaches using repair heuristics outperform existing EA approaches from the literature using penalties for infeasible solutions. They also find better solutions for existing problems from the literature, as well as for new and larger test problems.
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Balling, Richard J., Joseph C. Free i Alan R. Parkinson. "Consideration of Worst-Case Manufacturing Tolerances in Design Optimization". Journal of Mechanisms, Transmissions, and Automation in Design 108, nr 4 (1.12.1986): 438–41. http://dx.doi.org/10.1115/1.3258751.
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The paper discusses the effect of manufacturing tolerances for the design variables on the solution to an optimization problem. Two formulations of the tolerance problem in an optimization context are presented. Linearization is employed to reduce the problems to quadratic and linear programming problems. The formulations and solutions of the two tolerance problems are illustrated with an example application.
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Chen, Ta Cheng, i Tung-Chou Hsu. "An Immune Algorithm for Least Cost Advanced Tolerance Design Problem". Materials Science Forum 505-507 (styczeń 2006): 511–16. http://dx.doi.org/10.4028/www.scientific.net/msf.505-507.511.
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This paper considers nonlinearly mixed integer tolerance allocation problems in which both tolerance and process selection are to be decided simultaneously so as to minimize the manufacturing cost. The tolerance allocation problem has been studied in the literature for decades, usually using mathematical programming or heuristic/metaheuristic optimization approaches. The difficulties encountered for both methodologies are the number of constraints and the difficulty of satisfying the constraints. A penalty-guided artificial immune algorithm is presented for solving such mixed integer tolerance allocation problems. Numerical examples indicate that the proposed artificial immune algorithms perform well for the tolerance allocation problem considered in this paper. In particular, as reported, solutions obtained by artificial immune algorithm are as well as or better than the previously best-known solutions.
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Zahner, Doris, Jeffrey V. Nickerson, Barbara Tversky, James E. Corter i Jing Ma. "A fix for fixation? Rerepresenting and abstracting as creative processes in the design of information systems". Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24, nr 2 (26.04.2010): 231–44. http://dx.doi.org/10.1017/s0890060410000077.
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AbstractFixation prevents the associations that are bridges to new designs. The inability to see alternative solutions, or even to see how to map known solutions onto current problems, is a particularly acute problem in the design of software-intensive systems. Here, we explored two related ways of liberating fixated thinking: abstracting and rerepresenting. Although both techniques helped designers generate original ideas, not all the added ideas fit the problem constraints. We discuss ways the results might be used to generate reflective design aids that help designers to first generate original ideas and later prune them.
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Beckett, Stephen J. "The Logic of the Design Problem: A Dialectical Approach". Design Issues 33, nr 4 (październik 2017): 5–16. http://dx.doi.org/10.1162/desi_a_00470.
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This article analyzes the logic of the design problem by using a Hegelian dialectical approach. It begins by identifying the logical paradox at the heart of the design problem and clarifying the method of dialectical logic, and then applies this logic to the design problem by demonstrating how problems and solutions emerge simultaneously as “moments” of a single concept. Finally, the designer's role as a “speculative reader” in the process is briefly considered.
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Deb, Kalyanmoy, i Sachin Jain. "Multi-Speed Gearbox Design Using Multi-Objective Evolutionary Algorithms". Journal of Mechanical Design 125, nr 3 (1.09.2003): 609–19. http://dx.doi.org/10.1115/1.1596242.
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Optimal design of a multi-speed gearbox involves different types of decision variables and objectives. Due to lack of efficient classical optimization techniques, such problems are usually decomposed into tractable subproblems and solved. Moreover, in most cases the explicit mathematical expressions of the problem formulation is exploited to arrive at the optimal solutions. In this paper, we demonstrate the use of a multi-objective evolutionary algorithm, which is capable of solving the original problem involving mixed discrete and real-valued parameters and more than one objectives, and is capable of finding multiple nondominated solutions in a single simulation run. On a number of instantiations of the gearbox design problem having different complexities, the efficacy of NSGA-II in handling different types of decision variables, constraints, and multiple objectives are demonstrated. A highlight of the suggested procedure is that a post-optimal investigation of the obtained solutions allows a designer to discover important design principles which are otherwise difficult to obtain using other means.
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Gadó, Krisztián, i Tamás Orosz. "Robust and Multi-Objective Pareto Design of a Solenoid". Electronics 10, nr 17 (2.09.2021): 2139. http://dx.doi.org/10.3390/electronics10172139.
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The optimization of the design of a practical electromagnetic device involves many challenging tasks for new algorithms, especially those involving numerical modeling codes in which objective function calls must be minimized for practical design processes. The Compumag Society provides openly accessible, challenging benchmark problems (TEAM problems) for testing novel numerical solvers. This paper deals with a novel solution for the multi-objective TEAM benchmark problem. This solenoid design test problem aims to search for the optimal shape of a coil, which ensures a uniform field distribution in the control region, while the sensitivity and the mass/DC loss of the coil are also considered in the context of robust design. The main differences from the previously published solutions are that the proposed methodology optimizes all three objectives together, not only as two independent two-dimensional sub-problems. We considered the asymmetrical cases in the solution and found that the symmetrical solutions always produced better uniformity and sensitivity measures. However, the difference between the symmetrical and asymmetrical solutions is insignificant for these objectives. Despite the fact that the cheapest solutions are symmetrical setups, they perform worse than the cheapest asymmetric ones in these uniformity and sensitivity criteria. Therefore, some asymmetric solutions that were previously neglected from the solution space can be competitive and interesting for practical design.
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Su, Hai-Jun, Charles W. Wampler i J. Michael McCarthy. "Geometric Design of Cylindric PRS Serial Chains". Journal of Mechanical Design 126, nr 2 (1.03.2004): 269–77. http://dx.doi.org/10.1115/1.1667965.
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This paper considers the design of cylindric PRS serial chains. This five degree-of-freedom robot can be designed to reach an arbitrary set of eight spatial positions. However, it is often convenient to choose some of the design parameters and specify a task with fewer positions. For this reason, we study the three through eight position synthesis problems and consider various choices of design parameters for each. A linear product decomposition is used to obtain bounds on the number of solutions to these design problems. For all cases of six or fewer positions, the bound is exact and we give a reduction of the problem to the solution of an eigenvalue problem. For seven and eight position tasks, the linear product decomposition is useful for generating a start system for solving the problems by continuation. The large number of solutions so obtained contraindicates an elimination approach for seven or eight position tasks, hence continuation is the preferred approach.
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Zhang, Jinhuan, Margaret M. Wiecek i Wei Chen. "Local Approximation of the Efficient Frontier in Robust Design". Journal of Mechanical Design 122, nr 2 (1.03.2000): 232–36. http://dx.doi.org/10.1115/1.533571.
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The problem of robust design is treated as a bi-objective optimization problem in which the performance mean and variation are optimized and minimized, respectively. A method for deriving a utility function as a local approximation of the efficient frontier is presented and investigated at different locations of candidate solutions, with different ranges of interest, and for efficient frontiers with both convex and nonconvex behaviors. As an integral part of the interactive robust design procedure earlier proposed by the authors, the method assists designers in adjusting the preference structure and exploring alternative efficient robust design solutions. It eliminates the need of solving the bi-objective problem repeatedly using new preference structures, which is often computationally expensive. Though demonstrated for robust design problems, the principle is also applicable to any bi-objective optimization problem. [S1050-0472(00)00702-9]
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Narayanan, Soumya, i Sahana Murthy. "Flare-fork collaborative strategy: expanding design space via opportunistic ideation in engineering product design". Research and Practice in Technology Enhanced Learning 18 (17.09.2022): 003. http://dx.doi.org/10.58459/rptel.2023.18003.
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Restricted exploration of design space is a problem that novice designers face when solving engineering product design problems. Consequences of limited exploration can be the generation of sub-optimal solutions and fixation towards the first solution idea or known solution space. Expert designers sift through their vast repertoire of solution alternatives and choose the appropriate solution for the given design problem. Novices, however, lack this vast repository of alternative solution approaches. Therefore, it is good practice for novices to expand the problem and solution space and explore different aspects of the product design problem before identifying solutions appropriate for the design problem.
Flare-fork collaborative strategy is a design exploration strategy that enables designers to generate opportunistic ideas related to the design problem and integrate them during the design process thereby expanding problem and solution space. The flare-fork collaborative strategy leverages rapid ideation, and semantic analogy thought transformation strategy to generate new ideas, interlinking ideas in design space map (DSM) for the elaboration of ideas, and thought transformer strategy to manipulate ideas for expanding problem and solution space. This paper describes a study to examine how the operationalization of the flare aspect of flare-fork collaborative strategy as an intervention supports the design process of three teams of students. We found that students frequently traverse between problem and solution space via an intermediate bridge space. Also, regardless of where the students begin, they do a comprehensive exploration of problem and solution space while using flare-fork collaborative strategy. Students’ perception of using flare-fork collaborative strategy to explore engineering product design is predominantly positive, with students identifying several ways in which flare aspect of flare-fork collaborative strategy aided them in their expansion of problem and solution space.
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Deutsch, D. N. "Solutions to a Switchbox Routing Problem". IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 4, nr 2 (kwiecień 1985): 163. http://dx.doi.org/10.1109/tcad.1985.1270110.
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Li, Haibing, i Roland Lachmayer. "Automated Exploration of Design Solution Space Applying the Generative Design Approach". Proceedings of the Design Society: International Conference on Engineering Design 1, nr 1 (lipiec 2019): 1085–94. http://dx.doi.org/10.1017/dsi.2019.114.
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AbstractDesign is a complex problem-solving activity that transforms design restrictions and requirements into a set of constraints and explores the feasible solutions to satisfy those constraints. However, design solutions generated by traditional modeling approaches are hardly to deal with such constraints, particularly for the exploration of the possible design solution space to enhance the quality of the design outputs and confront the evolving design requirements. In this regard, the Generative Design Approach (GDA) is considered as an efficient method to explore a large design solution space by transforming the design problem into a configuration problem. Fundamentally, GDA explores and stores all the necessary knowledge through a design skeleton and a set of design elements. Thus, design solution space is easily explored by configuring variable design elements via iterative design processes. Further, the output model is not only a design solution but also a design concept that designers could manipulate to explore unconsidered design configurations. Finally, a crank creation as a running example confirmed that GDA provides concrete aids to enhance the diversity of design solutions.
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Fares, M'hand. "Renegotiation Design and Contract Solutions to the Hold-Up Problem". Journal of Economic Surveys 20, nr 5 (grudzień 2006): 731–56. http://dx.doi.org/10.1111/j.1467-6419.2006.00266.x.
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Redondo, Juana López, José Fernández, Inmaculada García i Pilar M. Ortigosa. "Solving the Multiple Competitive Facilities Location and Design Problem on the Plane". Evolutionary Computation 17, nr 1 (marzec 2009): 21–53. http://dx.doi.org/10.1162/evco.2009.17.1.21.
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A continuous location problem in which a firm wants to set up two or more new facilities in a competitive environment is considered. Other facilities offering the same product or service already exist in the area. Both the locations and the qualities of the new facilities are to be found so as to maximize the profit obtained by the firm. This is a global optimization problem, with many local optima. In this paper we analyze several approaches to solve it, namely, three multistart local search heuristics, a multistart simulated annealing algorithm, and two variants of an evolutionary algorithm. Through a comprehensive computational study it is shown that the evolutionary algorithms are the heuristics that provide the best solutions. Furthermore, using a set of problems for which the optimal solutions are known, only the evolutionary algorithms were able to find the optimal solutions for all the instances. The evolutionary strategies presented in this paper can be easily adapted to handle other continuous location problems.
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Chakrabarti, Amaresh, i Thomas P. Bligh. "An approach to functional synthesis of mechanical design Concepts: Theory, applications, and emerging research issues". Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10, nr 4 (wrzesień 1996): 313–31. http://dx.doi.org/10.1017/s0890060400001645.
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AbstractConceptual design is an early stage in the design process that involves the generation of solution concepts to satisfy the functional requirements of a design problem. Usually, there are many solutions to a design problem; therefore, there is scope for producing improved designs if one could explore a solution space larger than is presently possible. An approach would be to use the computer to synthesize a wide variety of concepts for a given problem, and allow designers to explore these before developing the most promising ones. Adopting a research approach based on developing basic representations, knowledge base, and reasoning procedures adequate for synthesizing concepts of existing devices and mechanisms, a computer program for synthesis of solutions to a class of mechanical design problems has been developed. For a given design problem, the program can produce an exhaustive set of solution concepts, in terms of their topological and spatial configurations, which can then be explored by designers. The program has been tested in two ways: (1) by comparing the candidate solutions produced by the program with those produced by designers in two real design case studies, and (2) by using three experienced designers to evaluate the solutions, generated by the program, for their novelty and usefulness. This paper presents the theoretical basis, research method, the theory and implementation of the synthesis approach. Also, the results of the above case studies and evaluations, and a discussion of further issues highlighted by the evaluations are presented.
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Agarwal, Sonal, Vidushi Sharma i Anuradha Pughat. "Supplier selection problem in IoT solutions". International Journal of Pervasive Computing and Communications 15, nr 1 (1.04.2019): 16–19. http://dx.doi.org/10.1108/ijpcc-d-18-00022.
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Purpose The use of Internet of Things (IoT) and networks has built a potential impact on the product cost and time in a company’s manufacturing process. These IoT solutions provide end-to-end visibility and faster introduction of merchandise and supplier in the market. The main aim of this research paper is to supply products with improved quality and cheaper price, whereas the rising response and quality of the client service. Design/methodology/approach This paper designs and develops two cases for selecting the most efficient vendor while keeping in mind the profit and cost constraints in optimization. Findings Outsourcing is a vital parameter to cut back the price and maximize the profit of the manufacturer. Therefore, the integration of supply chain with IoT can provide a solution to the cost optimization and supplier/vendor selection problems in supply chain management. Research limitations/implications The results show that the models are quite realistic and can help the IoT-based manufacturing units to make strategic decisions regarding product manufacturing and distribution. Practical implications The authors can further extend the model to derive the retailer’s profit function and develop the end product cost to the consumers and hence make it a n-level multi-vendor selection model for IoT-based systems. Originality/value The right choice of vendor for IoT-enabled business is a crucial concern. In this paper, the authors designed and developed multi-vendor models with in-house production and outsourcing decisions to meet the demand along with the vendor selection. The variable demands and designed variable unit cost function and batch order are set to make vendor selection more realistic.
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Laiprakobsup, Narongpon. "Research Collaboration with the Architectural Design Process: Co-Development of Problems and Solutions". Journal of Architectural/Planning Research and Studies (JARS) 10, nr 2 (7.08.2022): 15–30. http://dx.doi.org/10.56261/jars.v10i2.16767.
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This research aims to investigate what a possible framework design research can be integrated withthe architectural-design process. The process of design embodies dialectics between generation of form andresearch. How strategic design research is cooperative into design processes to achieve the design solutionhas been barely examined in a broad range of the architectural-design practices. The study thus explores acomparative analysis of the design processes in different design practice between third-year architecture students,fifth-year architecture students, and architects, to examine various forms of design research taking place infinding and solving problems.Findings reveal that design research lies in investigative modes and processing of external knowledgerelevant to problems, thereby enabling for a decisive solution. Research cooperates with the design process aslearning tensions between problems and solutions. However, the problem-solution pairing and research takingplace do not promise the successful solution. The acceptable design unfolds continuous improvement betweena series of problems-solutions through which research induces the co-development of problems-solutionsframework from an abstract idea to concrete levels of design development in three situations: “understandingcriteria and formulating goals,” “exploring possibility,” and “examining reality.” Moreover, practitioners mostly drawupon more design visions to direct problem-framing, research, and working methods to meet design goals thannovice students operate research into the process of design.To effectively implement research into the design process, a designer could consider design activity asa critical learning process as the co-development of problems-solutions framework to operate design strategiesand thinking. This mode of design thinking will allow design research roles to collaborate with problem-framingand design methods into the design process.
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Domek, G., A. Kołodziej, K. Warmbier i E. Gawrońska. "Design Problem of Flat Belts in Internal Transport Systems". International Journal of Engineering and Advanced Technology 10, nr 5 (30.06.2021): 158–62. http://dx.doi.org/10.35940/ijeat.d2533.0610521.
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The work deals with the problem of using flat belts in internal transport systems. There are many modern solutions for such belts, but to use them in demanding logistics systems, it is necessary to analyze the basic problems associated with coupling in a belt transmission. Then fast movement and transport problems can be solved. All these parameters contribute to the new approach to the belt-pulley coupling model, which was proposed in this paper.
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Corrales-Estrada, Martha. "Design thinkers’ profiles and design thinking solutions". Academia Revista Latinoamericana de Administración 33, nr 1 (14.06.2019): 9–24. http://dx.doi.org/10.1108/arla-01-2018-0028.
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Purpose The purpose of this paper is to understand how the profiles of design thinkers influence particular design-thinking solutions. It proposes to identify who (profiles), how (design-thinking methodologies) and what (outcomes as an innovation roadmap: process, product, business model, channel, brand, etc.), since the ways professional designers tackle a problem to reach an innovative solution is related to the designers’ profile. Design/methodology/approach The paper opted for an exploratory study using a focus group, composed of eight design thinkers and experts. An online survey was also sent to 123 DT leaders, with a return rate of 41 surveys, who worked on an end-to-end innovation project. The data were complemented by documentary analyses. Findings The paper provides empirical insights into the importance of selecting a diverse DT team. The team composition must be diverse because different profiles are required for different types of innovation and also for each DT phase to create value. Research limitations/implications Given the exploratory research approach being used in the paper, the research results may lack generalization to different contexts. Therefore, researchers are encouraged to test the proposed propositions further, using a larger sample that includes designers from different countries and testing eventual hypotheses. Practical implications The paper includes implications to increase the success rate of business innovations, and to reduce the associated costs that continue to increase for trial and error methods. Originality/value The paper fulfills an identified need to study how the DT profile and phases, empathize, define, ideate, prototype and test, require the correct skills and leadership throughout the whole process for effective outcome implementation.
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Katayama, Naoto. "MIP Neighborhood Search Heuristics for a Capacitated Fixed-Charge Network Design Problem". Asia-Pacific Journal of Operational Research 37, nr 03 (30.04.2020): 2050009. http://dx.doi.org/10.1142/s0217595920500098.
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The fixed-charge capacitated multicommodity network design problem is a fundamental optimization problem arising in many network configurations. The solution of the problem provides an appropriate network design as well as routes of multicommodity flows aimed at minimizing the total cost, which is the sum of the flow costs and fixed-charge costs over a network with limited arc capacities. In the present paper, we introduce a combined approach with a capacity scaling procedure for finding an initial feasible solution and an MIP neighborhood search for improving the solutions. Besides, we modify the procedure for application to large-scale problems. Computational experiments demonstrate the effectiveness of the proposed approach, and high-quality solutions are obtained for two problem sets from the literature.
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Raoui, Hanane El, Marcelino Cabrera-Cuevas i David A. Pelta. "The Role of Metaheuristics as Solutions Generators". Symmetry 13, nr 11 (28.10.2021): 2034. http://dx.doi.org/10.3390/sym13112034.
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Optimization problems are ubiquitous nowadays. Many times, their corresponding computational models necessarily leave out of consideration several characteristics and features of the real world, so trying to obtain the optimum solution can not be enough for a problem solving point of view. The aim of this paper is to illustrate the role of metaheuristics as solutions’ generators in a basic problem solving framework. Metaheuristics become relevant in two modes: firstly because every run (in the case of population based techniques) allows to obtain a set of potentially good solutions, and secondly, if a reference solution is available, one can set up a new optimization problem that allows to obtain solutions with similar quality in the objectives space but maximally different structure in the design space. Once a set of solutions is obtained, an example of an a posteriori analysis to rank them according with decision maker’s preferences is shown. All the problem solving framework steps, emphasizing the role of metaheuristics are illustrated with a dynamic version of the tourist trip design problem (for the first mode), and with a perishable food distribution problem (for the second one). These examples clearly show the benefits of the problem solving framework proposed. The potential role of the symmetry concept is also explored.
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Koishi, M., i Z. Shida. "Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2". Tire Science and Technology 34, nr 3 (1.09.2006): 170–94. http://dx.doi.org/10.2346/1.2345640.
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Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.
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Overmyer, Trinity, i Erin Brock Carlson. "Literature Review: Design Thinking and Place". Journal of Business and Technical Communication 33, nr 4 (11.06.2019): 431–36. http://dx.doi.org/10.1177/1050651919854079.
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Design-thinking frameworks help professionals to design solutions for complex problems. Design processes take into account the context of a problem, and among these contextual factors is place. Because place is relational, capturing dynamic relationships between other factors of design problems, it deserves special attention from stakeholders trying to tackle wicked problems. This literature review elaborates on the relationship between place and design thinking, focusing on the importance of privileging place in user-centered design processes.
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Loukianov, Alexander G. "Robust block decomposition sliding mode control design". Mathematical Problems in Engineering 8, nr 4-5 (2002): 349–65. http://dx.doi.org/10.1080/10241230306732.
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The paper examines the problem of sliding mode manifold design for uncertain nonlinear system with discontinuous control. The original plant first is decomposed such that the problem is divided into a number of simpler sub-problems. Then the block control recursive procedure is presented in which nonlinear sliding manifold is derived. Finally combined high gain and Lyapunov functions techniques are applied to establish hierarchy of the control gains and to estimate the upper bounds of the sliding mode equation solutions.
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Perricone, Valentina, Carlo Santulli, Francesco Rendina i Carla Langella. "Organismal Design and Biomimetics: A Problem of Scale". Biomimetics 6, nr 4 (28.09.2021): 56. http://dx.doi.org/10.3390/biomimetics6040056.
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Organisms and their features represent a complex system of solutions that can efficiently inspire the development of original and cutting-edge design applications: the related discipline is known as biomimetics. From the smallest to the largest, every species has developed and adapted different working principles based on their relative dimensional realm. In nature, size changes determine remarkable effects in organismal structures, functions, and evolutionary innovations. Similarly, size and scaling rules need to be considered in the biomimetic transfer of solutions to different dimensions, from nature to artefacts. The observation of principles that occur at very small scales, such as for nano- and microstructures, can often be seen and transferred to a macroscopic scale. However, this transfer is not always possible; numerous biological structures lose their functionality when applied to different scale dimensions. Hence, the evaluation of the effects and changes in scaling biological working principles to the final design dimension is crucial for the success of any biomimetic transfer process. This review intends to provide biologists and designers with an overview regarding scale-related principles in organismal design and their application to technical projects regarding mechanics, optics, electricity, and acoustics.
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COIT, DAVID W., i JIA CHEN LIU. "SYSTEM RELIABILITY OPTIMIZATION WITH k-OUT-OF-n SUBSYSTEMS". International Journal of Reliability, Quality and Safety Engineering 07, nr 02 (czerwiec 2000): 129–42. http://dx.doi.org/10.1142/s0218539300000110.
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Optimal solutions to the redundancy allocation problem are determined for systems designed with multiple k-out-of-n subsystems in series. The objective is to select the components and redundancy levels to maximize system reliability given system-level constraints. The individual subsystems may use either active or cold-standby redundancy, or they may require no redundancy. Previously, optimization methods for this problem either pertained to k-out-of-n systems consisting of a single subsystem or to series–parallel systems (k=1). Additionally, it had generally been assumed that only active redundancy was to be used. In practice design problems can vary appreciably from these restrictions and the design process may consider more complex system configurations. Unfortunately, available optimization algorithms are inadequate for many of these design problems. The methodology presented here is specifically developed to accommodate the case with k-out-of-n subsystems. Optimal solutions to the problem are found by an equivalent problem formulation and integer programming. The methodology is demonstrated on a well-known test problem with interesting results. The availability of this tool fills a void and should result in more reliable and cost-effective engineering designs.
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Yoshida, Toru, i Tomohiro Yoshikawa. "Analysis of Pareto Solutions Based on Non-Correspondence in Spread Between Objective Space and Design Variable Space". Journal of Advanced Computational Intelligence and Intelligent Informatics 19, nr 5 (20.09.2015): 681–87. http://dx.doi.org/10.20965/jaciii.2015.p0681.
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Recently, many studies have been conducted on Multi-Objective Genetic Algorithm (MOGA), in which Genetic Algorithms are applied to Multi-objective Optimization Problems (MOPs). Among various applications, MOGA is also applied to engineering design problems, which require not only high-performance Pareto solutions to be obtained, but also an analysis of the obtained Pareto solutions and extraction of design knowledge about the problem itself. In order to analyze the Pareto solutions obtained by MOGA, it is necessary to consider the objective space and the design variable space. The aim of this study is to extract and analyze solutions of relevant interest to designers. In this paper, we propose three solutions to analyze and extract design knowledge from MOGA. (1) We define “Non-Correspondence in Spread” between the objective space and the design variable space. (2) We try to extract the Non-Correspondence area in Spread using the index defined in this paper. (3) We apply the defined index to genetic search to obtain Pareto solutions that have different design variables and similar fitness values. This paper applies the above index to the trajectory design optimization problem and extracts Non-Correspondence area in Spread from the obtained Pareto solutions. This paper also shows that robust Pareto solutions can be obtained using genetic search using the defined index.
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Zhang, Wenlin, i Jin Ma. "DESIGNING IN COMPLEXITY: HOW SOLUTION CONJECTURES INFORM PROBLEM EXPLORATION". Proceedings of the Design Society 1 (27.07.2021): 1153–62. http://dx.doi.org/10.1017/pds.2021.115.
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AbstractEngineering designers seek to explore ‘real’ problems that must be solved across design processes. This exploration might be challenging in complex problem situations. An effective way of encouraging design exploration is conjecture-based problem exploration—informing problem re-interpretation by potential solutions. However, little evidence indicated how this process unfolds, especially in complex problem situations. This study addresses this question by articulating the underlying cognitive mechanism of conjecture-based problem exploration. Situated in a creative design practice that tackles real-world, complex problem situations, we employ grounded theory to conduct qualitative coding of interview transcripts and documents elicited from ten multidisciplinary graduate students. We developed a three-phase process model to explain conjecture-based problem exploration: (1) triggering through analogizing, inspiring, evaluating, and questioning; (2) transitioning to problem space expansion; and (3) resulting in problem focus adjustment incrementally or radically. Our explanation contributes to design theory building and encourages engineering designers to embrace a dynamic view of design problems when addressing complexity.
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Soto, Ricardo, Broderick Crawford, Jose M. Lanza-Gutierrez, Rodrigo Olivares, Pablo Camacho, Gino Astorga, Hanns de la Fuente-Mella, Fernando Paredes i Carlos Castro. "Solving the Manufacturing Cell Design Problem through an Autonomous Water Cycle Algorithm". Applied Sciences 9, nr 22 (6.11.2019): 4736. http://dx.doi.org/10.3390/app9224736.
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Metaheuristics are multi-purpose problem solvers devoted to particularly tackle large instances of complex optimization problems. However, in spite of the relevance of metaheuristics in the optimization world, their proper design and implementation to reach optimal solutions is not a simple task. Metaheuristics require an initial parameter configuration, which is dramatically relevant for the efficient exploration and exploitation of the search space, and therefore to the effective finding of high-quality solutions. In this paper, the authors propose a variation of the water cycle inspired metaheuristic capable of automatically adjusting its parameter by using the autonomous search paradigm. The goal of our proposal is to explore and to exploit promising regions of the search space to rapidly converge to optimal solutions. To validate the proposal, we tested 160 instances of the manufacturing cell design problem, which is a relevant problem for the industry, whose objective is to minimize the number of movements and exchanges of parts between organizational elements called cells. As a result of the experimental analysis, the authors checked that the proposal performs similarly to the default approach, but without being specifically configured for solving the problem.
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LORENA, ANA C., i ANDRÉ C. P. L. F. de CARVALHO. "EVALUATION FUNCTIONS FOR THE EVOLUTIONARY DESIGN OF MULTICLASS SUPPORT VECTOR MACHINES". International Journal of Computational Intelligence and Applications 08, nr 01 (marzec 2009): 53–68. http://dx.doi.org/10.1142/s146902680900245x.
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Support Vector Machines were originally proposed to solve two-class classification problems. When they are applied to multiclass classification problems, usually a decomposition approach is followed, in which the original multiclass problem is decomposed into multiple binary sub-problems, whose solutions are afterwards combined. There are several strategies to decompose the multiclass problem. Genetic Algorithms (GAs) can be used to optimize the decomposition according to the performance obtained in the overall multiclass problem solution. This paper presents a study on possible evaluation functions that can be used by the GA in order to evaluate a given decomposition.
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El Alem, W., A. El Hami i Rachid Ellaia. "Pareto-Optimal Solutions for a Truss Problem". Advanced Materials Research 423 (grudzień 2011): 53–64. http://dx.doi.org/10.4028/www.scientific.net/amr.423.53.
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Most optimization problems, particularly those in engineering design, require the simultaneous optimization of more than one objective function. In this context, the solutions of these problems are based on the Pareto frontier construction. Substantial efforts have been made in recent years to develop methods for the construction of Pareto frontiers that guarantee uniform distribution and exclude the non-Pareto and local Pareto points. The Normal Boundary Intersection (NBI) is a recent contribution that generates a well-distributed Pareto frontier efficiently. Nevertheless, this method should be combined with a global optimization method to ensure the convergence to the global Pareto frontier. This paper proposes the NBI method using Adaptive Simulated Annealing (ASA) algorithm, namely NBI-ASA as a global nonlinear multi-objective optimization method. A well known benchmark multi-objective problem has been chosen from the literature to demonstrate the validity of the proposed method, applicability of the method for structural problems has been tested through a truss problem and promising results were obtained. The results indicate that the proposed method is a powerful search and multi-objective optimization technique that may yield better solutions to engineering problems than those obtained using current algorithms.
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Lamé, Guillaume, Bernard Yannou i François Cluzel. "Usage-driven problem design for radical innovation in healthcare". BMJ Innovations 4, nr 1 (24.11.2017): 15–23. http://dx.doi.org/10.1136/bmjinnov-2016-000149.
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While the diffusion and evaluation of healthcare innovations receive a lot of attention, the early design stages are less studied and potential innovators lack methods to identify where new innovations are necessary and to propose concepts relevant to users. To change this, we propose a structured methodology, Radical Innovation Design (RID), which supports designers who want to work on the unstated needs of potential end users in order to create superior value. In this article, the first part of RID is introduced with its two subprocesses: Problem Design and Knowledge Design. In this first period, RID guides innovators to systematically explore users’ problems and evaluate which ones are most pressing in terms of innovation, taking into account existing solutions. The result is an ambition perimeter, composed of a set of value buckets, that is, important usage situations where major problems are experienced and the current solutions provide little or no relief. The methodology then moves on to Solution Design and Business Design (which are not detailed in this article) to address the value buckets identified. With its emphasis on problem exploration, RID differs from methods based on early prototyping. The RID methodology has been validated in various industrial sectors and is well-adapted for healthcare innovation. To exemplify the methodology, we present a case study in dental imagery performed by 10 students in 8 weeks. This example demonstrates how RID favours efficiency in Problem Design and allows designers to explore unaddressed and sometimes undeclared user needs.
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Khouzani, MHR, i Pasquale Malacaria. "Optimal Channel Design: A Game Theoretical Analysis". Entropy 20, nr 9 (5.09.2018): 675. http://dx.doi.org/10.3390/e20090675.
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This paper studies the problem of optimal channel design. For a given input probability distribution and for hard and soft design constraints, the aim here is to design a (probabilistic) channel whose output leaks minimally from its input. To analyse this problem, general notions of entropy and information leakage are introduced. It can be shown that, for all notions of leakage here defined, the optimal channel design problem can be solved using convex programming with zero duality gap. Subsequently, the optimal channel design problem is studied in a game-theoretical framework: games allow for analysis of optimal strategies of both the defender and the adversary. It is shown that all channel design problems can be studied in this game-theoretical framework, and that the defender’s Bayes–Nash equilibrium strategies are equivalent to the solutions of the convex programming problem. Moreover, the adversary’s equilibrium strategies correspond to a robust inference problem.
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Togay, Abdullah, Merve Coşkun, Serkan Güneş i Çiğdem Güneş. "Computer aided design in education and its’ interpretation through design thinking". New Trends and Issues Proceedings on Humanities and Social Sciences 2, nr 1 (19.02.2016): 328–37. http://dx.doi.org/10.18844/prosoc.v2i1.315.
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The notion of “design thinking†can be regarded as a way of thinking that consists of both divergent and convergent phases. As a creative problem solving methodology, it first defines the problem with a human-centered perspective and then analyzes all the aspects of the problem as a part of a whole. This approach can be applied in all fields, including design education. With the emerging technology, computer-aided design tools and techniques have become an indispensable part of design professions, and therefore education. However, the way how computer-aided design tools and techniques should be integrated into current design education has not been discussed adequately. This study aims to frame the problems related to the current content, structure and timing of CAD courses. The alternative solutions regarding the integration of CAD courses to product design education will be proposed by using design thinking method.Keywords: design thinking, computer aided design (CAD), design educationÂ
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Morgan, A. P., i C. W. Wampler. "Solving a Planar Four-Bar Design Problem Using Continuation". Journal of Mechanical Design 112, nr 4 (1.12.1990): 544–50. http://dx.doi.org/10.1115/1.2912644.
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The problem of synthesizing a planar 4-bar with given pivots such that the coupler curve passes through five precision points is considered. It is shown that the design parameters must satisfy a system of 4 fourth-degree polynomial equations in 4 unknowns which has at most 36 nonzero real solutions. This polynomial system is solved using a continuation method, which thereby generates the collection of all designs that meet the precision-point specification. A computer program that implements this continuation method has been tested on a number of problems. It is reliable and fast enough for the purposes of design. The approach to kinematic design represented by this work is completely general, subject only to computer-time limitations that may arise for problems with many design elements.
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Álvarez-Miranda, Eduardo, Valentina Cacchiani, Andrea Lodi, Tiziano Parriani i Daniel R. Schmidt. "Single-commodity robust network design problem: Complexity, instances and heuristic solutions". European Journal of Operational Research 238, nr 3 (listopad 2014): 711–23. http://dx.doi.org/10.1016/j.ejor.2014.04.023.
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Lalvani, Haresh. "Meta-Morphological Technique for a Multi-Parameter Design Index". International Journal of Space Structures 8, nr 4 (grudzień 1993): 241–49. http://dx.doi.org/10.1177/026635119300800402.
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Complex design and morphologic problems, consisting of multiple parameters, can be described, modelled and indexed using a meta-morphological technique presented here. All design and morphologic variables can be mapped in Euclidean n-dimensional space, where n is the number of variables. This meta-space contains all the possible solutions to the problem and each point in this solution n-space is a candidate solution. The desired solution, represented by a specific point in this space and coded (addressed) by its n-dimension Cartesian co-ordinates, is ranked by the hyper-distance of this point from the origin. The hyper-distance itself provides a design index (or hyper-index) of the solution and can be determined by the known hyper-Pythagorean theorem. The procedure is recursive and applies to complex design problems which are hierarchical and composed of problem-within-problem-within-problems. Here the parameters are composed of subparameters, and the solutions are correspondingly mapped in a recursive, fractal n-cube composed of sub-cubes composed of sub-sub-cubes. The total composite index is determined by the recursive application of the hyper-Pythagorean theorem and represents a quantification of the morphological complexity of the design. The model is independent of the design problem, and has attractive possibilities for application in computer-aided design environments. The application is shown with the hypothetical selection of a space frame from a number of alternatives.
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BAHEEL, Jasim Khazaal. "DESIGN THINKING AND ITS CREATIVE STRATEGIES IN INDUSTRIAL DESIGN". RIMAK International Journal of Humanities and Social Sciences 03, nr 07 (1.09.2021): 35–47. http://dx.doi.org/10.47832/2717-8293.7-3.4.
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The research discussed the concept of design thinking based on its relationship with the design specialist and its intellectual methods in analyzing phenomena to find solutions to the problems of the physical world in which we live, by identifying the foundations of design knowledge from studying humanistic theories and patterns of human thinking, through the cognitive references to the concept of design thinking, which was defined by cognitive modeling Creative thinking and designedly ways of thinking. And we found that design thinking is a mental strategy through which the design specialist intends to exhibit phenomena to find solutions to them, a strategy that differs from scientific and other artistic strategies. As this strategy adopts logical thinking related to the real world and creative imagination linked to the technical aspects of problem solving. The research found that this mental strategy is used in other disciplines based on creative thinking in achieving its products, such as business management and competition between companies. The research offer a group of creative strategies that have the ability to develop creative thinking for design professionals and other creative specializations.
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Ruiz-Meza, José, Julio Brito, Jairo R. Montoya-Torres i Ana Castro-Vergara. "Green Fuzzy Tourist Trip Design Problem". Advances in Operations Research 2022 (24.06.2022): 1–10. http://dx.doi.org/10.1155/2022/6828385.
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The shift from mass tourism to more personalized travel denotes great importance in the construction of tourist itineraries. Given the negative impacts of transport and tourism on the environment, sustainability criteria play an important role. The Tourist Trip Design Problem is related to the design of itineraries for tourists. Planning is complex in tourist regions of developing countries where the information associated with tourist activities is difficult to access, vague, and incomplete. With this information, tourists must plan their trip, and the conditions and limitations they establish for it are flexible and imprecise. Fuzzy optimization can address problems with this type of information and constraints. Therefore, in this paper, an analysis of the tourism supply chain is carried out, taking as a case study the Department of Sucre on Colombia's Caribbean coast. A Multiconstraint Multimodal Team Orienteering Problem with Time Windows and fuzzy constraints is developed to model the tourism trip design problem that maximizes profit and minimizes CO2 emissions. The model is tested using datasets from the literature and the real world. The results demonstrate consistency with the fuzzy approach and generate a set of low-emission solutions.