Journal articles: 'Generalized Assignment Problems'

1

Mazzola, J. B., and A. W. Neebe. "Bottleneck generalized assignment problems." Engineering Costs and Production Economics 14, no. 1 (May 1988): 61–65. http://dx.doi.org/10.1016/0167-188x(88)90053-5.

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Narciso, Marcelo G., and Luiz Antonio N. Lorena. "Lagrangean/surrogate relaxation for generalized assignment problems." European Journal of Operational Research 114, no. 1 (April 1999): 165–77. http://dx.doi.org/10.1016/s0377-2217(98)00038-1.

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Osorio, Marı́a A., and Manuel Laguna. "Logic cuts for multilevel generalized assignment problems." European Journal of Operational Research 151, no. 1 (November 2003): 238–46. http://dx.doi.org/10.1016/s0377-2217(02)00576-3.

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4

Wu, Wen Bo, Yu Fu Jia, and Hong Xing Sun. "A Determinant Elimination Method for Bottleneck Assignment and Generalized Assignment Problems." Applied Mechanics and Materials 239-240 (December 2012): 1522–27. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1522.

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The bottleneck assignment (BA) and the generalized assignment (GA) problems and their exact solutions are explored in this paper. Firstly, a determinant elimination (DE) method is proposed based on the discussion of the time and space complexity of the enumeration method for both BA and GA problems. The optimization algorithm to the pre-assignment problem is then discussed and the adjusting and transformation to the cost matrix is adopted to reduce the computational complexity of the DE method. Finally, a synthesis method for both BA and GA problems is presented. The numerical experiments are carried out and the results indicate that the proposed method is feasible and of high efficiency.

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Albareda-Sambola, Maria, Maarten H. van der Vlerk, and Elena Fernández. "Exact solutions to a class of stochastic generalized assignment problems." European Journal of Operational Research 173, no. 2 (September 2006): 465–87. http://dx.doi.org/10.1016/j.ejor.2005.01.035.

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Litvinchev, Igor, Miguel Mata, Socorro Rangel, and Jania Saucedo. "Lagrangian heuristic for a class of the generalized assignment problems." Computers & Mathematics with Applications 60, no. 4 (August 2010): 1115–23. http://dx.doi.org/10.1016/j.camwa.2010.03.070.

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Sharkey, Thomas C., and H. Edwin Romeijn. "Greedy approaches for a class of nonlinear Generalized Assignment Problems." Discrete Applied Mathematics 158, no. 5 (March 2010): 559–72. http://dx.doi.org/10.1016/j.dam.2009.11.002.

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Hallefjord, Åsa, Kurt O. Jörnsten, and Peter Värbrand. "Solving large scale generalized assignment problems — An aggregation / disaggregation approach." European Journal of Operational Research 64, no. 1 (January 1993): 103–14. http://dx.doi.org/10.1016/0377-2217(93)90011-b.

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Simić, Petar D. "Constrained Nets for Graph Matching and Other Quadratic Assignment Problems." Neural Computation 3, no. 2 (June 1991): 268–81. http://dx.doi.org/10.1162/neco.1991.3.2.268.

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Some time ago Durbin and Willshaw proposed an interesting parallel algorithm (the “elastic net”) for approximately solving some geometric optimization problems, such as the Traveling Salesman Problem. Recently it has been shown that their algorithm is related to neural networks of Hopfield and Tank, and that they both can be understood as the semiclassical approximation to statistical mechanics of related physical models. The main point of the elastic net algorithm is seen to be in the way one deals with the constraints when evaluating the effective cost function (free energy in the thermodynamic analogy), and not in its geometric foundation emphasized originally by Durbin and Willshaw. As a consequence, the elastic net algorithm is a special case of the more general physically based computations and can be generalized to a large class of nongeometric problems. In this paper we further elaborate on this observation, and generalize the elastic net to the quadratic assignment problem. We work out in detail its special case, the graph matching problem, because it is an important problem with many applications in computational vision and neural modeling. Simulation results on random graphs, and on structured (hand-designed) graphs of moderate size (20-100 nodes) are discussed.

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Litvinchev, I. S., and S. Rangel. "Comparison of Lagrangian bounds for one class of generalized assignment problems." Computational Mathematics and Mathematical Physics 48, no. 5 (May 2008): 739–46. http://dx.doi.org/10.1134/s0965542508050047.

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Jeet, V., and E. Kutanoglu. "Lagrangian relaxation guided problem space search heuristics for generalized assignment problems." European Journal of Operational Research 182, no. 3 (November 2007): 1039–56. http://dx.doi.org/10.1016/j.ejor.2006.09.060.

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Elhay, Sylvan. "Symmetry preserving partial pole assignment for the standard and generalized eigenvalue problems." ANZIAM Journal 49 (July 22, 2007): 264. http://dx.doi.org/10.21914/anziamj.v48i0.106.

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Kogan, Konstantin, Eugene Khmelnitsky, and Toshihide Ibaraki. "Dynamic Generalized Assignment Problems with Stochastic Demands and Multiple Agent--Task Relationships." Journal of Global Optimization 31, no. 1 (January 2005): 17–43. http://dx.doi.org/10.1007/s10898-004-4273-3.

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Tapkan, Pınar, Lale Özbakır, and Adil Baykasoğlu. "Solving fuzzy multiple objective generalized assignment problems directly via bees algorithm and fuzzy ranking." Expert Systems with Applications 40, no. 3 (February 2013): 892–98. http://dx.doi.org/10.1016/j.eswa.2012.05.045.

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Phudphad, Phattaraphorn, Kanchana Sethanan, and Thitipong Jamrus. "A hybrid particle swarm optimization for the generalized assignment problem with time window." MATEC Web of Conferences 192 (2018): 01015. http://dx.doi.org/10.1051/matecconf/201819201015.

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This study focuses on the inbound logistics of the sugarcane industry, which has three main procedures consisting of cultivation, harvest and transportation. Generally, small-scale growers cannot manage all of the procedures effectively, because of their lack of bargaining power and inadequate equipment. For this reason a resource-sharing policy, such as harvester and truck sharing, is used by factories to reduce the cost of the sugarcane harvest, and increase harvester and truck utilization. To solve the generalized assignment problem (GAP) with time window, thus minimizing the total cost from the assignment of the third-party logistics providers to service small-scale growers under capacity and time limitations, a mathematical model has been developed for small-sized problems. For large-scale problems, particle swarm optimization (PSO) is applied and improved by the hybridization of PSO with k-cyclic moves algorithm (PSOK). The results demonstrate that the proposed metaheuristics can solve the problem efficiently since the results are equal to, or close to, the optimal solutions in which the averaged performances of PSO and PSOK are 99.61% and 99.64%, respectively and the averaged relative improvement is 0.1519%.

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HIGGINS, A. J. "A PERCENTILE SEARCH HEURISTIC FOR GENERALIZED ASSIGNMENT PROBLEMS WITH A VERY LARGE NUMBER OF JOBS." Asia-Pacific Journal of Operational Research 22, no. 02 (June 2005): 171–88. http://dx.doi.org/10.1142/s0217595905000492.

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This article presents a new heuristic for generalized assignment problems with a very large number of jobs. The heuristic applies a probabilistic acceptance of a move, based on a percentile threshold, using information from recent moves. This percentile search heuristic (PSH) is compared to tabu search, simulated annealing, and threshold accepting using a rigorous computational experimentation with randomly generated problem instances of up to 50,000 jobs and 40 agents. The PSH did find the best solution among the heuristics for 45% of the instances, particularly larger size problems, versus 30% for tabu search, but required more fine-tuning of the heuristic parameters.

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Ghoniem, Ahmed, Tulay Flamand, and Mohamed Haouari. "Optimization-Based Very Large-Scale Neighborhood Search for Generalized Assignment Problems with Location/Allocation Considerations." INFORMS Journal on Computing 28, no. 3 (July 2016): 575–88. http://dx.doi.org/10.1287/ijoc.2016.0703.

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18

Kumar. "A New Method for Solving Fuzzy Generalized Assignment Problems with L-R Type Fuzzy Parameters." Journal of Advanced Research in Applied Mathematics 3, no. 2 (April 1, 2011): 74–84. http://dx.doi.org/10.5373/jaram.647.112410.

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Bektur, Gülçin. "A multi-start iterated tabu search algorithm for the multi-resource agent bottleneck generalized assignment problem." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 10, no. 1 (October 6, 2019): 37–46. http://dx.doi.org/10.11121/ijocta.01.2020.00796.

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In this study, a multi-resource agent bottleneck generalized assignment problem (MRBGAP) is addressed. In the bottleneck generalized assignment problem (BGAP), more than one job can be assigned to an agent, and the objective function is to minimize the maximum load over all agents. In this problem, multiple resources are considered and the capacity of the agents is dependent on these resources and it has minimum two indices. In addition, agent qualifications are taken into account. In other words, not every job can be assignable to every agent. The problem is defined by considering the problem of assigning jobs to employees in a firm. BGAP has been shown to be NP- hard. Consequently, a multi-start iterated tabu search (MITS) algorithm has been proposed for the solution of large-scale problems. The results of the proposed algorithm are compared by the results of the tabu search (TS) algorithm and mixed integer linear programming (MILP) model.

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He, Hongyu, Yanzhi Zhao, Xiaojun Ma, Zheng-Guo Lv, and Ji-Bo Wang. "Branch-and-Bound and Heuristic Algorithms for Group Scheduling with Due-Date Assignment and Resource Allocation." Mathematics 11, no. 23 (November 23, 2023): 4745. http://dx.doi.org/10.3390/math11234745.

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Green scheduling that aims to enhance efficiency by optimizing resource allocation and job sequencing concurrently has gained growing academic attention. To tackle such problems with the consideration of scheduling and resource allocation, this paper considers a single-machine group scheduling problem with common/slack due-date assignment and a controllable processing time. The objective is to decide the optimized schedule of the group/job sequence, resource allocation, and due-date assignment. To solve the generalized case, this paper proves several optimal properties and presents a branch-and-bound algorithm and heuristic algorithms. Numerical experiments show that the branch-and-bound algorithm is efficient and the heuristic algorithm developed based on the analytical properties outruns the tabu search.

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Staruch, Bożena, and Bogdan Staruch. "Competence-based assignment of tasks to workers in factories with demand-driven manufacturing." Central European Journal of Operations Research 29, no. 2 (February 18, 2021): 553–65. http://dx.doi.org/10.1007/s10100-021-00739-4.

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AbstractThe paper is motivated by real problems concerning tasks assignment to workers in medium-sized upholstered furniture plants managed using the Demand-Driven Manufacturing. Although the methodology was developed for furniture plants it can be applied to other types of production plants. We involve competence coefficients, which describe the level of the worker’s skills or capabilities to perform a specific task. The competence coefficients are also used to block the possibility of assigning the given task to a worker that has no skills to do it. Additionally, we involve a dummy worker to the model which guarantees the existence of a solution to the problem. We present and discuss Integer Linear Programming Models for the posted problem that are closely related to the Generalized Assignment Problem. We also discuss the potential use of the presented methodology to solve real-life problems related to production management.

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Lee, Jungwoo, Youngho Choi, and Jinho Suh. "DeConNet: Deep Neural Network Model to Solve the Multi-Job Assignment Problem in the Multi-Agent System." Applied Sciences 12, no. 11 (May 27, 2022): 5454. http://dx.doi.org/10.3390/app12115454.

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In a multi-agent system, multi-job assignment is an optimization problem that seeks to minimize total cost. This can be generalized as a complex problem in which several variations of vehicle routing problems are combined, and as an NP-hard problem. The parameters considered include the number of agents and jobs, the loading capacity, the speed of the agents, and the sequence of consecutive positions of jobs. In this study, a deep neural network (DNN) model was developed to solve the job assignment problem in a constant time regardless of the state of the parameters. To generate a large training dataset for the DNN, the planning domain definition language (PDDL) was used to describe the problem, and the optimal solution that was obtained using the PDDL solver was preprocessed into a sample of the dataset. A DNN was constructed by concatenating the fully-connected layers. The assignment solution obtained via DNN inference increased the average traveling time by up to 13% compared with the ground cost. As compared with the ground cost, which required hundreds of seconds, the DNN execution time was constant at approximately 20 ms regardless of the number of agents and jobs.

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23

Yantsevich, M. A., and H. A. Filipovich. "THE METOD OF SYNTHESIS OF QUASI-DUAL-BAND MATCHING DEVICE." Doklady BGUIR 18, no. 2 (March 31, 2020): 71–79. http://dx.doi.org/10.35596/1729-7648-2020-18-2-71-79.

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The article presents some findings on the potential of analytical methods for the synthesis of broadband matching circuits for solving nontrivial circuit engeneering problems. Nontriviality shows itself in the technique for the assignment of the frequency response model (approximation) for the broadband synthesis in cellular communication, when double-band antennas are essential. The frequency response model appears as the result of frequency transformation, which yields in the assignment of both bands at the very first stage of the synthesis. The bands’width and isolation between them may be controlled independently, which is the essential part of the frequency transformation. Such way offrequency response assignment allows the potential of the method, which is always restricted by a load, to find broader application. In these conditions the frequency response turns to a quasi-double and asymmetrical one due to finite isolation between bands. We also present the general approach to the synthesis, which incorporates both the frequency transformation and novel synthesis technique. The modified frequency transformation can be applied to all types oftraditional approximations of arbitrary orders in synthesizing broadband frequency-selective matching devices. The distinctive feature of this technique is in the use of generalized Darlington’s synthesis for solving the problems of broadband matching of resistances in a lumped element basis with the application of frequency reponses obtained through modified frequency transformation. We have also estimated the efficiency of the developed technique by comparison with the known results.

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Ishtaiwi, Abdelraouf, Feda Alshahwan, Naser Jamal, Wael Hadi, and Muhammad AbuArqoub. "A Dynamic Clause Specific Initial Weight Assignment for Solving Satisfiability Problems Using Local Search." Algorithms 14, no. 1 (January 5, 2021): 12. http://dx.doi.org/10.3390/a14010012.

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For decades, the use of weights has proven its superior ability to improve dynamic local search weighting algorithms’ overall performance. This paper proposes a new mechanism where the initial clause’s weights are dynamically allocated based on the problem’s structure. The new mechanism starts by examining each clause in terms of its size and the extent of its link, and its proximity to other clauses. Based on our examination, we categorized the clauses into four categories: (1) clauses small in size and linked with a small neighborhood, (2) clauses small in size and linked with a large neighborhood, (3) clauses large in size and linked with a small neighborhood, and (4) clauses large in size and linked with a large neighborhood. Then, the initial weights are dynamically allocated according to each clause category. To examine the efficacy of the dynamic initial weight assignment, we conducted an extensive study of our new technique on many problems. The study concluded that the dynamic allocation of initial weights contributes significantly to improving the search process’s performance and quality. To further investigate the new mechanism’s effect, we compared the new mechanism with the state-of-the-art algorithms belonging to the same family in terms of using weights, and it was clear that the new mechanism outperformed the state-of-the-art clause weighting algorithms. We also show that the new mechanism could be generalized with minor changes to be utilized within the general-purpose stochastic local search state-of-the-art weighting algorithms.

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Wang, Chenxi, M. J. A. Khan, M. Ibrahim, E. Bonyah, M. K. Siddiqui, and S. Khalid. "On Edge Irregular Reflexive Labeling for Generalized Prism." Journal of Mathematics 2022 (March 7, 2022): 1–7. http://dx.doi.org/10.1155/2022/2886555.

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Among the various ideas that appear while studying graph theory, which has gained much attraction especially in graph labeling, labeling of graphs gives mathematical models which value for a vast range of applications in high technology (data security, cryptography, various problems of coding theory, astronomy, data security, telecommunication networks, etc.). A graph label is a designation of graph elements, i.e., the edges and/or vertex of a group of numbers (natural numbers), and is called assignment or labeling. The vertex or edge labeling is related to their domain asset of vertices or edges. Likewise, for total labeling, we take the domain as vertices and edges both at the same time. The reflexive edge irregularity strength (res) is total labeling in which weights of edges are not the same for all edges and the weight of an edge is taken as the sum of the edge labels and the vertices associated with that edge. In the res, the vertices are labeled with nonnegative even integers while the edges are labeled with positive integers. We have to make the labels minimum, whether they are associated with vertices or edges. If such labeling exists, then it is called the res of H and is represented as s res H . In this paper, we have computed the res for the Cartesian product of path and cycle graph which is also known as generalizing prism.

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Li, Xinyi, Junmin Mou, Linying Chen, Yamin Huang, and Pengfei Chen. "Ship–Infrastructure Cooperation: Survey on Infrastructure Scheduling for Waterborne Transportation Systems." Journal of Marine Science and Engineering 11, no. 1 (December 27, 2022): 31. http://dx.doi.org/10.3390/jmse11010031.

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Ship–infrastructure cooperation, i.e., infrastructure scheduling, is significant for optimizing the utilization of spatial-temporal resources of infrastructures and improving the efficiency and safety of waterborne transportation systems. This paper carries out a systematic review of the scheduling problems of the infrastructures in waterborne transportation systems, including locks, terminals, berths, and waterway intersections. The infrastructure scheduling problems are linked to the classical optimization problems, and a generalized infrastructure scheduling problem is formulated. For lock scheduling, the ship placement sub-problem aims at minimizing the number of lockages, which is a kind of classic 2D bin packing problem; the lockage scheduling sub-problem deals with chamber assignment and lockage operation planning, which is modeled as a single or parallel machine scheduling problem. For berth and terminal scheduling, the idea of queuing theory (for discrete terminal) and 2D bin packing (for continuous terminal) are usually applied. Most research aims at minimizing the waiting time of ships and focuses on the continuous dynamic terminal scheduling problems. As a special infrastructure, the waterway intersection receives little attention. Most research focuses on traffic conflicts and capacity problems. Future research directions are provided based on the review results and problems of infrastructure scheduling in practice.

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Sutton, Andrew M., Francisco Chicano, and L. Darrell Whitley. "Fitness Function Distributions over Generalized Search Neighborhoods in the q-ary Hypercube." Evolutionary Computation 21, no. 4 (November 2013): 561–90. http://dx.doi.org/10.1162/evco_a_00098.

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The frequency distribution of a fitness function over regions of its domain is an important quantity for understanding the behavior of algorithms that employ randomized sampling to search the function. In general, exactly characterizing this distribution is at least as hard as the search problem, since the solutions typically live in the tails of the distribution. However, in some cases it is possible to efficiently retrieve a collection of quantities (called moments) that describe the distribution. In this paper, we consider functions of bounded epistasis that are defined over length-n strings from a finite alphabet of cardinality q. Many problems in combinatorial optimization can be specified as search problems over functions of this type. Employing Fourier analysis of functions over finite groups, we derive an efficient method for computing the exact moments of the frequency distribution of fitness functions over Hamming regions of the q-ary hypercube. We then use this approach to derive equations that describe the expected fitness of the offspring of any point undergoing uniform mutation. The results we present provide insight into the statistical structure of the fitness function for a number of combinatorial problems. For the graph coloring problem, we apply our results to efficiently compute the average number of constraint violations that lie within a certain number of steps of any coloring. We derive an expression for the mutation rate that maximizes the expected fitness of an offspring at each fitness level. We also apply the results to the slightly more complex frequency assignment problem, a relevant application in the domain of the telecommunications industry. As with the graph coloring problem, we provide formulas for the average value of the fitness function in Hamming regions around a solution and the expectation-optimal mutation rate.

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Ohsaki, Makoto, and Kentaro Hayakawa. "Non-Parametric Shape Design of Free-Form Shells Using Fairness Measures and Discrete Differential Geometry." Journal of the International Association for Shell and Spatial Structures 62, no. 2 (June 1, 2021): 93–101. http://dx.doi.org/10.20898/j.iass.2021.007.

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A non-parametric approach is proposed for shape design of free-form shells discretized into triangular mesh. The discretized forms of curvatures are used for computing the fairness measures of the surface. The measures are defined as the area of the offset surface and the generalized form of the Gauss map. Gaussian curvature and mean curvature are computed using the angle defect and the cotangent formula, respectively, defined in the field of discrete differential geometry. Optimization problems are formulated for minimizing various fairness measures for shells with specified boundary conditions. A piecewise developable surface can be obtained without a priori assignment of the internal boundary. Effectiveness of the proposed method for generating various surface shapes is demonstrated in the numerical examples.

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Rasmussen, Rasmus. "Minimizing Costs Can Be Costly." Advances in Decision Sciences 2010 (March 7, 2010): 1–16. http://dx.doi.org/10.1155/2010/707504.

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A quite common practice, even in academic literature, is to simplify a decision problem and model it as a cost-minimizing problem. In fact, some type of models has been standardized to minimization problems, like Quadratic Assignment Problems (QAPs), where a maximization formulation would be treated as a “generalized” QAP and not solvable by many of the specially designed softwares for QAP. Ignoring revenues when modeling a decision problem works only if costs can be separated from the decisions influencing revenues. More often than we think this is not the case, and minimizing costs will not lead to maximized profit. This will be demonstrated using spreadsheets to solve a small example. The example is also used to demonstrate other pitfalls in network models: the inability to generally balance the problem or allocate costs in advance, and the tendency to anticipate a specific type of solution and thereby make constraints too limiting when formulating the problem.

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Prashker, J. N., and S. Bekhor. "Investigation of Stochastic Network Loading Procedures." Transportation Research Record: Journal of the Transportation Research Board 1645, no. 1 (January 1998): 94–102. http://dx.doi.org/10.3141/1645-12.

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The network loading process of stochastic traffic assignment is investigated. A central issue in the assignment problem is the behavioral assumption governing route choice, which concerns the definition of available routes and the choice model. These two problems are addressed and reviewed. Although the multinomial logit model can be implemented efficiently in stochastic network loading algorithms, the model suffers from theoretical drawbacks, some of them arising from the independence of irrelevant alternatives property. As a result, the stochastic loading on routes that share common links is overloaded at the overlapping parts of the routes. Other logit-family models recently have been proposed to overcome some of the theoretical problems while maintaining the convenient analytical structure. Three such models are investigated: the C-logit model, which was specifically defined for route choice; and two general discrete-choice models, the cross-nested logit model and the paired combinatorial logit model. The two latter models are adapted to route choice, and simple network examples are presented to illustrate the performance of the models with respect to the overlapping problem. The results indicate that all three models perform better than does the multinomial logit model. The cross-nested logit model has an advantage over the two other generalized models because it enables performing stochastic loading without route enumeration. The integration of this model with the stochastic equilibrium problem is discussed, and a specific algorithm using the cross-nest logit model is presented for the stochastic loading phase.

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Sergeev, Aleksei N. "Learning in Online Communities: Behavioral Strategies of the Users of Educational Social Networks." International Journal of Criminology and Sociology 10 (December 31, 2020): 84–92. http://dx.doi.org/10.6000/1929-4409.2021.10.12.

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The article deals with the results of a study on users’ behavioral strategies in educational social networks as Internet platforms for the communities of students and teachers who collaborate to solve educational problems. According to the analysis of the students and teachers’ activity on the educational social network of the Volgograd State Socio-Pedagogical University, the author has determined the groups of users with similar behavioral strategies, namely: community organizers, activists for communication and document exchange, educational assignment performers, information consumers, and inactive users. The author provides generalized portraits of each group, their numerical composition, as well as comparative characteristics in relation to other groups. The manuscript concludes that the presented groups reveal typical behavioral strategies of the users of educational social networks, which further development of educational platform tools, as well as pedagogical technologies based on their implementation should consider.

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Traverso, A., A. F. Massardo, M. Santarelli, and M. Cali. "A New Generalized Carbon Exergy Tax: An Effective Rule to Control Global Warming." Journal of Engineering for Gas Turbines and Power 125, no. 4 (October 1, 2003): 972–78. http://dx.doi.org/10.1115/1.1610013.

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An instrument for promoting CO2 emission reductions, taking the Kyoto Protocol goal into account, could be the assignment to energy conversion plants of a monetary charge linked to their specific emission intensity, usually called carbon tax. There are two main problems closely connected with this approach: the estimation of the charge (that must be related to the “external” cost associated with CO2 emission) and the choice of the strategy to determine the amount of the imposed charge. In this paper an analytical procedure proposed by the authors and called carbon exergy tax (CET) for the evaluation of CO2 emission externalities is presented. It is based on the thermoeconomic analysis of energy systems, which allows second law losses to be quantified in monetary terms: the resulting cost represents the taxation that is to be applied to the energy system under examination, calculated without any arbitrary assumption. Since the complete procedure of the CET evaluation is too complex to become a feasible instrument of energy policy, hereby, after applying the procedure to some conventional and advanced power plants, gas, oil, and coal-fueled, a new generalized approach, based on the results of the complete CET procedure, is proposed. The generalized CET evaluation requires much less information about the energy system and thus a simple and effective energy policy rule to manage global warming is obtained and available.

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Chen, Yutong, and Yongchuan Tang. "An Improved Approach of Incomplete Information Fusion and Its Application in Sensor Data-Based Fault Diagnosis." Mathematics 9, no. 11 (June 4, 2021): 1292. http://dx.doi.org/10.3390/math9111292.

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The Dempster–Shafer evidence theory has been widely used in the field of data fusion. However, with further research, incomplete information under the open world assumption has been discovered as a new type of uncertain information. The classical Dempster’s combination rules are difficult to solve the related problems of incomplete information under the open world assumption. At the same time, partial information entropy, such as the Deng entropy is also not applicable to deal with problems under the open world assumption. Therefore, this paper proposes a new method framework to process uncertain information and fuse incomplete data. This method is based on an extension to the Deng entropy in the open world assumption, negation of basic probability assignment (BPA), and the generalized combination rule. The proposed method can solve the problem of incomplete information under the open world assumption, and obtain more uncertain information through the negative processing of BPA, which improves the accuracy of the results. The results of applying this method to fault diagnosis of electronic rotor examples show that, compared with the other uncertain information processing and fusion methods, the proposed method has wider adaptability and higher accuracy, and is more conducive to practical engineering applications.

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Maniezzo, Vittorio, and Tingting Zhou. "Learning Individualized Hyperparameter Settings." Algorithms 16, no. 6 (May 26, 2023): 267. http://dx.doi.org/10.3390/a16060267.

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The performance of optimization algorithms, and consequently of AI/machine learning solutions, is strongly influenced by the setting of their hyperparameters. Over the last decades, a rich literature has developed proposing methods to automatically determine the parameter setting for a problem of interest, aiming at either robust or instance-specific settings. Robust setting optimization is already a mature area of research, while instance-level setting is still in its infancy, with contributions mainly dealing with algorithm selection. The work reported in this paper belongs to the latter category, exploiting the learning and generalization capabilities of artificial neural networks to adapt a general setting generated by state-of-the-art automatic configurators. Our approach differs significantly from analogous ones in the literature, both because we rely on neural systems to suggest the settings, and because we propose a novel learning scheme in which different outputs are proposed for each input, in order to support generalization from examples. The approach was validated on two different algorithms that optimized instances of two different problems. We used an algorithm that is very sensitive to parameter settings, applied to generalized assignment problem instances, and a robust tabu search that is purportedly little sensitive to its settings, applied to quadratic assignment problem instances. The computational results in both cases attest to the effectiveness of the approach, especially when applied to instances that are structurally very different from those previously encountered.

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Loureiro, Carlos Felipe G., and Bruce Ralston. "Investment Selection Model for Multicommodity Multimodal Transportation Networks." Transportation Research Record: Journal of the Transportation Research Board 1522, no. 1 (January 1996): 38–46. http://dx.doi.org/10.1177/0361198196152200105.

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A Multicommodity Multimodal Network Design (MCMND) model is presented; the model is to be used as a planning tool for determining investment priorities for freight intercity networks. The MCMND model is designed to select the best set of investment options for a multimodal regional network, given a limited investment budget. The main component of the model comprises the solution of a nonlinear bilevel network design problem formulated to choose investments that minimize both the transportation costs incurred by users and the environmental impacts of less efficient modes of transportation. Investment options to be considered by the model involve the addition of new physical links to the network, the improvement of existing links, and the location of intermodal transfer facilities at specified nodes of the network. The representation of the multimodal network is at a level of detail appropriate for strategic planning for a large region. The demand for transportation services is fixed and exogenous to the model. Mode choice in shipping freight is modeled in combination with flow assignment, assuming that goods are shipped at minimum total generalized costs. A new path-based stochastic user equilibrium assignment algorithm is proposed to distribute trips over the multimodal network according to a logit-type model. The Tietê-Paraná Valley in Brazil was selected for the development of a pilot application of the MCMND model to assess its efficiency when dealing with large networks. This application also served to emphasize the importance of an interface between the MCMND model and a geographic information system in solving real-life problems.

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Lesik, Ilya. "Market’s static model for software development based on a transport problem with non-fixed time additions." Economics and the Mathematical Methods 58, no. 2 (2022): 97. http://dx.doi.org/10.31857/s042473880019969-4.

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The authors describe the formulation of the market’s discrete-continuous static model for software development based on a transport problem with non-fixed time additions. In contrast to the existing transport problem with fixed cost surcharges, it is proposed to formulate a minimax setting in time with times that may contain a part that proportionate to the volumes of appointments. Thus, the authors come up with the idea of a hybrid formulation of transport problem with fixed cost surcharges and classical transport problem in time. Such problems arise when the total volume of vehicles which have to be used repeatedly on each route is limited, plus the fixed addition that arises taking into account the delay in making logistics decisions. It is shown that the set a discrete-continuous problem can be approximated from above by the classical transport problem in time, which can also be obtained according to the scheme used in the work by Balinski. The authors also describe an exact algorithm of the branch-and-bound method, based on the geometric interpretation of the problem, which decomposes into subproblems on non-empty faces of the polyhedral set of feasible solutions, which areconvex programming problems that can be numerically solved by the subgradient method described in work by Polyak. The calculation of the lower estimates of the criterion proposed in the work is reduced to the same problems. It is shown that the function of the best values of the criterion on the edges is not sub- or supermodular, as a function of a subset of pairs of indices corresponding to the positive values of the transportation volumes, which makes it impossible to use supermodular programming methods. In connection with the latter, the authors also describe the optimal polynomial version of the branch-and-bound method, obtained by analogy with the solution of the multidimensional assignment problem, and a numerical example of its use. The authors describe interpretation of transport problem with non-fixed additions as a generalized assignment problem with non-fixed price discounts, taking into account the difference between the wholesale and retail prices. The authors come up with the ideaof the application for building digital platforms in the software development market for loading tasks for performers.

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S., Subasri. "Fuzzy Assignment Problem with Ranking of Generalized Nonagonal Fuzzy Number Using Centroid of Centroid." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (March 31, 2020): 978–83. http://dx.doi.org/10.5373/jardcs/v12sp4/20201570.

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Albers, Susanne, Arindam Khan, and Leon Ladewig. "Improved Online Algorithms for Knapsack and GAP in the Random Order Model." Algorithmica 83, no. 6 (February 17, 2021): 1750–85. http://dx.doi.org/10.1007/s00453-021-00801-2.

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AbstractThe knapsack problem is one of the classical problems in combinatorial optimization: Given a set of items, each specified by its size and profit, the goal is to find a maximum profit packing into a knapsack of bounded capacity. In the online setting, items are revealed one by one and the decision, if the current item is packed or discarded forever, must be done immediately and irrevocably upon arrival. We study the online variant in the random order model where the input sequence is a uniform random permutation of the item set. We develop a randomized (1/6.65)-competitive algorithm for this problem, outperforming the current best algorithm of competitive ratio 1/8.06 (Kesselheim et al. in SIAM J Comput 47(5):1939–1964, 2018). Our algorithm is based on two new insights: We introduce a novel algorithmic approach that employs two given algorithms, optimized for restricted item classes, sequentially on the input sequence. In addition, we study and exploit the relationship of the knapsack problem to the 2-secretary problem. The generalized assignment problem (GAP) includes, besides the knapsack problem, several important problems related to scheduling and matching. We show that in the same online setting, applying the proposed sequential approach yields a (1/6.99)-competitive randomized algorithm for GAP. Again, our proposed algorithm outperforms the current best result of competitive ratio 1/8.06 (Kesselheim et al. in SIAM J Comput 47(5):1939–1964, 2018).

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Mahmassani, Hani S., Xuesong Zhou, and Chung-Cheng Lu. "Toll Pricing and Heterogeneous Users." Transportation Research Record: Journal of the Transportation Research Board 1923, no. 1 (January 2005): 28–36. http://dx.doi.org/10.1177/0361198105192300104.

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This paper presents both exact and approximation algorithms for finding extreme efficient time-dependent shortest paths for use with dynamic traffic assignment applications to networks with variable toll pricing and heterogeneous users (with different value of time preferences). A parametric least-generalized cost path algorithm is presented to determine a complete set of extreme efficient time-dependent paths that simultaneously consider travel time and cost criteria. However, exact procedures may not be practical for large networks. For this reason, approximation schemes are devised and tested. Based on the concept of ε-efficiency in multiobjective shortest path problems, a binary search framework is developed to find a set of extreme efficient paths that minimize expected approximation error, with the use of the underlying value of time distribution. Both exact and approximation schemes (along with variants) are tested on three actual traffic networks. The experimental results indicate that the computation time and the size of the solution set are jointly determined by several key parameters such as the number of time intervals and the number of nodes in the network. The results also suggest that the proposed approximation scheme is computationally efficient for large-scale bi-objective time-dependent shortest path applications while maintaining satisfactory solution quality.

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Smedberg, Henrik, Carlos Alberto Barrera-Diaz, Amir Nourmohammadi, Sunith Bandaru, and Amos H. C. Ng. "Knowledge-Driven Multi-Objective Optimization for Reconfigurable Manufacturing Systems." Mathematical and Computational Applications 27, no. 6 (December 9, 2022): 106. http://dx.doi.org/10.3390/mca27060106.

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Current market requirements force manufacturing companies to face production changes more often than ever before. Reconfigurable manufacturing systems (RMS) are considered a key enabler in today’s manufacturing industry to cope with such dynamic and volatile markets. The literature confirms that the use of simulation-based multi-objective optimization offers a promising approach that leads to improvements in RMS. However, due to the dynamic behavior of real-world RMS, applying conventional optimization approaches can be very time-consuming, specifically when there is no general knowledge about the quality of solutions. Meanwhile, Pareto-optimal solutions may share some common design principles that can be discovered with data mining and machine learning methods and exploited by the optimization. In this study, the authors investigate a novel knowledge-driven optimization (KDO) approach to speed up the convergence in RMS applications. This approach generates generalized knowledge from previous scenarios, which is then applied to improve the efficiency of the optimization of new scenarios. This study applied the proposed approach to a multi-part flow line RMS that considers scalable capacities while addressing the tasks assignment to workstations and the buffer allocation problems. The results demonstrate how a KDO approach leads to convergence rate improvements in a real-world RMS case.

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Öztürk, Melike, and Çiğdem Alabaş-Uslu. "Cantor set based neighbor generation method for permutation solution representation." Journal of Intelligent & Fuzzy Systems 39, no. 5 (November 19, 2020): 6157–68. http://dx.doi.org/10.3233/jifs-189086.

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Metaheuristics gained world-wide popularity and researchers have been studying them vigorously in the last two decades. A relatively less explored approach in the improvement of metaheuristics is to design new neighbor generation mechanisms. Neighbor generation mechanisms are very important in the success of any single solution-based heuristic since they directly guide the search. In this study, a neighbor generation mechanism called cantor-set based (CB) method for single solution-based heuristics which use permutation solution representation is described. The inspiration for CB method stems from the recursive algorithm that constructs a cantor set which is a fractal set. Three variations of CB method are discussed (CB-1, CB-2, CB-3) considering the presented design possibilities. The computational experiments are conducted by embedding the mechanisms into the classical local search and simulated annealing algorithms, separately, to test their efficiency and effectiveness by comparing them to classical swap and insertion mechanisms. The traveling salesman problem (TSP) and quadratic assignment problem (QAP) which are very different problems that have incompatible characteristics have been chosen to test the mechanisms and sets of benchmark instances with varying sizes are chosen for the comparisons. The computational tests show that CB-2 gives very favorable results for TSP and CB-1 gives favorable results for QAP which means that CB-2 is suitable for problems that have steep landscapes and CB-1 is suitable for the problems that have flat landscapes. It is observed that CB-3 is a more generalized mechanism because it gives consistently good results for both TSP and QAP instances. The best mechanism for a given instance of the both problem types outperforms the classical neighbor generation of swap and insertion in terms of effectiveness.

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Lovin, D., I. Saveliev, and V. Strelets. "FORMATION OF A SET OF GOALS FOR THE SIMULATION EVALUATION OF THE SYSTEM "RESCUER - MEANS OF PROTECTION AND PROVISION OF EMERGENCY AND RESCUE WORK - EMERGENCY SITUATION"." Municipal economy of cities 6, no. 173 (December 16, 2022): 148–53. http://dx.doi.org/10.33042/2522-1809-2022-6-173-148-153.

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It was noted that an important and unsolved part of the problem of the inconsistency of the new tasks faced by the rescuers working under the conditions of today's additional restrictions to the conditions of using a wide variety of fire and rescue equipment in the rescue unit is the lack of a general approach to the formation of a set of goals for assessing what how well the "emergency situation - emergency rescue operations - rescuer" system functions, according to the results of simulation (both physical and with the help of computer) modeling. It is emphasized that the assignment of the properties of the system "emergency situation - emergency rescue operations - rescuer" is a necessary but not sufficient condition for solving the problems of evaluating this system. These properties must be combined into defined aggregates or expressed in the form of generalized integral characteristics. Such generalized characteristics are the quality indicators of such a system, i.e., a set of its properties that express the degree of usefulness of the system for the external environment at the output of the simulation system. It is noted that the tasks of evaluating the system "emergency situation - emergency rescue work - rescuer" can be checking the suitability of this system for its purpose, comparing such systems of the same type, deciding on the continuation (termination) of the development of such a system or adopting a ready-made system, determining the prospects of a specific system and evaluating compliance of its real state with the normative one. At the same time, the external efficiency criterion represents the regularity of personnel activity in the "emergency situation - emergency rescue operations - rescuer" system, as it reflects the functioning of this system, establishing an objective, repeated under certain conditions connection between the quality indicators of the system and those inherent in it effects The goals of the simulation evaluation of the system "emergency situation - emergency rescue operations - rescuer" are substantiated, as which it is necessary to consider the establishment of cause-and-effect relationships between the activities of rescuers and the results of the functioning of this system, the determination of the functional dependence of the system's generalized efficiency indicator on a set of selected initial indicators and further clarification based on the obtained functional dependence of such system organization rules, in which the specified value of the generalized efficiency indicator will be exceeded. Keywords: simulation assessment, system, emergency rescue operations, efficiency.

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Thongkham, Malichan, and Sasitorn Kaewman. "Methodology to Solve the Combination of the Generalized Assignment Problem and the Vehicle Routing Problem: A Case Study in Drug and Medical Instrument Sales and Service." Administrative Sciences 9, no. 1 (December 26, 2018): 3. http://dx.doi.org/10.3390/admsci9010003.

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This article presents algorithms for solving a special case of the vehicle routing problem (VRP). We define our proposed problem of a special VRP case as a combination of two hard problems: the generalized assignment and the vehicle routing problem. The different evolution (DE) algorithm is used to solve the problem. The recombination process of the original DE is modified by adding two more sets of vectors—best vector and random vector—and using two other sets—target vector and trial vector. The linear probability formula is proposed to potentially use one out of the four sets of vectors. This is called the modified DE (MDE) algorithm. Two local searches are integrated into the MDE algorithm: exchange and insert. These procedures create a DE and MDE that use (1) no local search techniques, (2) two local search techniques, (3) only the exchange procedure, and (4) only the insert procedure. This generates four DE algorithms and four MDE algorithms. The proposed methods are tested with 15 tested instances and one case study. The current procedure is compared with all proposed heuristics. The computational result shows that, in the case study, the best DE algorithm (DE-4) has a 1.6% better solution than that of the current practice, whereas the MDE algorithm is 8.2% better. The MDE algorithm that uses the same local search as the DE algorithms generates a maximum 5.814% better solution than that of the DE algorithms.

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Atserias, Albert, Phokion G. Kolaitis, and Simone Severini. "Generalized satisfiability problems via operator assignments." Journal of Computer and System Sciences 105 (November 2019): 171–98. http://dx.doi.org/10.1016/j.jcss.2019.05.003.

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Levchenko, K. B., and M. M. Lehenka. "Urgent restraining and restrictive orders as special response forms for domestic violence: international experience and national practice." Law and Safety 71, no. 4 (December 27, 2018): 60–65. http://dx.doi.org/10.32631/pb.2018.4.08.

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The authors of the article have substantiated the importance of the prevention of domestic violence and proper response to such cases in accordance with European and world standards. The authors have analyzed international experience of introducing restrictive measures for the persons who have committed domestic violence and the differences between urgent restraining and restrictive orders provided by the Law of Ukraine “On Prevention and Combating Domestic Violence” in order to create conditions for their effective application in practice. The authors have also analyzed the content of the restrictive order regarding the abuser as established by the court procedure as a mean of temporal restriction of the rights or the assignment of duties to a person who committed domestic violence aimed at ensuring the safety of the victim. The authors have characterized the urgent restraining order as a special measure to counteract domestic violence, which is used by the authorized units of the National Police of Ukraine as a response to the fact of domestic violence and aimed at its immediate termination, elimination of the danger to the lives and health of victims and preventing the continuation or re-execution of such violence. The procedures of application of the above mentioned orders have been provided. The comparative and legal analysis of the restrictive and urgent restraining orders has been carried out. International experience of applying a protective order in combating domestic violence has been generalized; reference to the relevant regulatory acts has been provided. It has been noted that the current stage of normative and legal, organizational and law-enforcement provision for combating domestic violence in Ukraine is characterized by both significant progress and serious problems that impede the mentioned progress. These problems are largely in the field of lawmaking and require more attention to the adoption of relevant regulatory acts.

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Sukmaningrum, Rahmawati, Arso Setyaji, and Faiza Hawa. "Students’ Challenges in Translating Poetry." Borneo Educational Journal (Borju) 5, no. 2 (June 19, 2023): 192–203. http://dx.doi.org/10.24903/bej.v5i2.1314.

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This article drawn from the local tracking study of how college students perceive the process of translating poetry. The aim of this study is to investigate the students’ challenge in translating poetry. The current study based upon the benefit of understanding poetry to build harmony in the society. Writers used descriptive qualitative research as the design of this study. The subject of the study were the sixth semester students of English Education Department of Universitas PGRI Semarang who had passed the Translation 1 subject and join the Translation 2 at the present time. The population of this study was 143 students in sixth semester. Writers then chose 20 students as the sample of this study. Students were assigned to translate English poem entitled ‘Huesca’ into Indonesian. The poem was written by John Conford, an American soldier who was endured on World War. After the assignment project, they were asked to respond the questionnaire related to the process of translating the poem and problems encountered. The finding revealed that most of students admitted that their biggest problem in poetry translation is associated with the linguistic difference. It refers to grammatical differences (source language and target language), lexical choices and meaning ambiguity. There were many factors behind the problems that encounter students in translating the English poem into Indonesian. Factors related to the culture, the use of figurative language, and the different structure between original poem and the target language are considered as main hindrances in translating literary works. The educational implication of the study is that our students need to be familiarized with literary works and its process of translation. However, since this study was only held in 2 months and had limited participants, the result of the study cannot be generalized. Further research, therefore, need to conduct by other researcher in order to get broader insight toward the theme

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Higgins, A. J. "A dynamic tabu search for large-scale generalised assignment problems." Computers & Operations Research 28, no. 10 (September 2001): 1039–48. http://dx.doi.org/10.1016/s0305-0548(00)00024-1.

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R., Feshchur, and Sosnova N. "EVALUATION OF THE GENERAL ATTRACTIVENESS OF THE URBAN PUBLIC SPACE ACCORDING TO MANY CRITERIA." Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Arhìtektura 2, no. 2 (November 2020): 193–203. http://dx.doi.org/10.23939/sa2020.02.193.

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Cities are constantly changing – new and existing facilities are created and reconstructed, existing ones are modernized, and new territories are developed, and, accordingly, public spaces are formed and develop in a certain way. To a large extent, this process is random and does not take place systematically, but this rather happens as a response to the urgent economic, environmental, social or other needs of city residents. Development management in the urban planning system is designed to solve the controversial problem of maintaining integrity and at the same time striving for its transformation. The use of the tools of mathematical modeling, considered in the article, allows one to solve the problems of spatial development of a city and its public spaces in a purposeful way, and to coordinate such a solution with the interests of stakeholders. When forming public spaces of a city one faces the task of streamlining competing development projects (alternative projects) for a particular area of a city, taking into account the importance of their impact on the establishment of a distinctive image of the city and ensuring quality of life of its residents. To solve this problem, it is advisable to use methods of expert evaluation of design decisions, in particular, methods of ranking, valuating, and folding vector-valued criterion into a scalar criterion (integrated indicator of project weight). Ranking means assignment of a certain rank (a number from the natural series) to every project. The most important project is given the highest rank, which corresponds to number "one". The sum of the ranks given by all experts to a particular project can be considered as a generalized value of its weight. The article considers approaches to the assessment of urban public spaces on the basis of various criteria, namely urban, social, economic, environmental ones. The developed models of public space planning are designed for making a reasonable choice from a set of alternative projects subject to implementation, either according to the dominant criterion or according to many criteria in the conditions of resource constraints.

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Cardone, Barbara, Ferdinando Di Martino, and Vittorio Miraglia. "A Novel Fuzzy-Based Remote Sensing Image Segmentation Method." Sensors 23, no. 24 (December 5, 2023): 9641. http://dx.doi.org/10.3390/s23249641.

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Image segmentation is a well-known image processing task that consists of partitioning an image into homogeneous areas. It is applied to remotely sensed imagery for many problems such as land use classification and landscape changes. Recently, several hybrid remote sensing image segmentation techniques have been proposed that include metaheuristic approaches in order to increase the segmentation accuracy; however, the critical point of these approaches is the high computational complexity, which affects time and memory consumption. In order to overcome this criticality, we propose a fuzzy-based image segmentation framework implemented in a GIS-based platform for remotely sensed images; furthermore, the proposed model allows us to evaluate the reliability of the segmentation. The Fast Generalized Fuzzy c-means algorithm is implemented to segment images in order to detect local spatial relations between pixels and the Triple Center Relation validity index is used to find the optimal number of clusters. The framework elaborates the composite index to be analyzed starting by multiband remotely sensed images. For each cluster, a segmented image is obtained in which the pixel value represents, transformed into gray levels, the graph belonging to the cluster. A final thematic map is built in which the pixels are classified based on the assignment to the cluster to which they belong with the highest membership degree. In addition, the reliability of the classification is estimated by associating each class with the average of the membership degrees of the pixels assigned to it. The method was tested in the study area consisting of the south-western districts of the city of Naples (Italy) for the segmentation of composite indices maps determined by multiband remote sensing images. The segmentation results are consistent with the segmentations of the study area by morphological and urban characteristics, carried out by domain experts. The high computational speed of the proposed image segmentation method allows it to be applied to massive high-resolution remote sensing images.

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Sumita, Hanna, Shinji Ito, Kei Takemura, Daisuke Hatano, Takuro Fukunaga, Naonori Kakimura, and Ken-ichi Kawarabayashi. "Online Task Assignment Problems with Reusable Resources." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 5 (June 28, 2022): 5199–207. http://dx.doi.org/10.1609/aaai.v36i5.20455.

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We study online task assignment problem with reusable resources, motivated by practical applications such as ridesharing, crowdsourcing and job hiring. In the problem, we are given a set of offline vertices (agents), and, at each time, an online vertex (task) arrives randomly according to a known time-dependent distribution. Upon arrival, we assign the task to agents immediately and irrevocably. The goal of the problem is to maximize the expected total profit produced by completed tasks. The key features of our problem are (1) an agent is reusable, i.e., an agent comes back to the market after completing the assigned task, (2) an agent may reject the assigned task to stay the market, and (3) a task may accommodate multiple agents. The setting generalizes that of existing work in which an online task is assigned to one agent under (1). In this paper, we propose an online algorithm that is 1/2-competitive for the above setting, which is tight. Moreover, when each agent can reject assigned tasks at most Δ times, the algorithm is shown to have the competitive ratio Δ/(3Δ-1), which is at least 1/3. We also evaluate our proposed algorithm with numerical experiments.

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Journal articles on the topic 'Generalized Assignment Problems'

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