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Автор: Grafiati
Опубліковано: 30 травня 2022
Оновлено: 31 травня 2022

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Статті в журналах з теми "Heuristics methods"

1

Wilt, Christopher, and Wheeler Ruml. "Effective Heuristics for Suboptimal Best-First Search." Journal of Artificial Intelligence Research 57 (October 31, 2016): 273–306. http://dx.doi.org/10.1613/jair.5036.

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Анотація:
Suboptimal heuristic search algorithms such as weighted A* and greedy best-first search are widely used to solve problems for which guaranteed optimal solutions are too expensive to obtain. These algorithms crucially rely on a heuristic function to guide their search. However, most research on building heuristics addresses optimal solving. In this paper, we illustrate how established wisdom for constructing heuristics for optimal search can fail when considering suboptimal search. We consider the behavior of greedy best-first search in detail and we test several hypotheses for predicting when a heuristic will be effective for it. Our results suggest that a predictive characteristic is a heuristic's goal distance rank correlation (GDRC), a robust measure of whether it orders nodes according to distance to a goal. We demonstrate that GDRC can be used to automatically construct abstraction-based heuristics for greedy best-first search that are more effective than those built by methods oriented toward optimal search. These results reinforce the point that suboptimal search deserves sustained attention and specialized methods of its own.
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2

Cichowicz, T., M. Drozdowski, M. Frankiewicz, G. Pawlak, F. Rytwinski, and J. Wasilewski. "Hyper-heuristics for cross-domain search." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 4 (December 1, 2012): 801–8. http://dx.doi.org/10.2478/v10175-012-0093-7.

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Abstract In this paper we present two hyper-heuristics developed for the Cross-Domain Heuristic Search Challenge. Hyper-heuristics solve hard combinatorial problems by guiding low level heuristics, rather than by manipulating problem solutions directly. Two hyper-heuristics are presented: Five Phase Approach and Genetic Hive. Development paths of the algorithms and testing methods are outlined. Performance of both methods is studied. Useful and interesting experience gained in construction of the hyper-heuristics are presented. Conclusions and recommendations for the future advancement of hyper-heuristic methodologies are discussed.
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3

Abdul-Razaq, Tariq, Hanan Chachan, and Faez Ali. "Modified Heuristics for Scheduling in Flow Shop to Minimize Makespan." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 2 (October 19, 2021): 1–20. http://dx.doi.org/10.55562/jrucs.v30i2.361.

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Анотація:
The NP-completeness of flow shops scheduling problems has been discussed for many years. Hence many heuristics have been proposed to obtain solutions of good quality with a small computational effort. The CDS (Campbell et al) and NEH (Nawaz, Enscore and Ham) heuristics are efficient among meta-heuristics such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).This paper discusses some methods and suggests new developing to the methods of the scheduling in flow shop to minimize makespan problems. Our main object in this paper, from one side, is to improve efficient heuristics which will be better than the existing heuristics given in the literature and yield solutions within a short time like Simple Heuristic Methods (SHM) and the First Heuristic Decreasing Arrange (DR). From other side, we apply two local search methods like GA and PSO algorithms on flow shop problems.Experimental analysis has been given of the performance of the proposed heuristics and local search methods with the relative efficient existing heuristics.
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4

Shanklin, Roslyn, Philip Kortum, and Claudia Ziegler Acemyan. "Adaptation of Heuristic Evaluations for the Physical Environment." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (December 2020): 1135–39. http://dx.doi.org/10.1177/1071181320641272.

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Previous work has investigated the need for domain specific heuristics. Nielsen’s ten heuristics offer a general list of principles, but those principles may not capture usability issues specific to a given interface. Studies have demonstrated methods to establish a domain specific heuristic set, but very little research has been conducted on interfaces in the physical environment, creating a gap in the state-of-the-art. The research described in this paper aims to address this gap by developing an environmental heuristic set; the heuristic set was developed specifically for the Houston light rail system, METRORail. Following development, the heuristic set was validated against Nielsen’s more general heuristics through several field studies. Results highlighted that there were significantly more usability issues identified when using the environment-based heuristics than the general heuristics. This suggests that domain specific heuristics provide a framework that allows evaluators to capture usability issues particular to the interface of the physical environment.
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5

Triki, C. "Solution Methods for the Periodic Petrol Station Replenishment Problem." Journal of Engineering Research [TJER] 10, no. 2 (December 1, 2013): 69. http://dx.doi.org/10.24200/tjer.vol10iss2pp69-77.

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In this paper we introduce the Periodic Petrol Station Replenishment Problem (PPSRP) over a T-day planning horizon and describe four heuristic methods for its solution. Even though all the proposed heuristics belong to the common partitioning-then-routing paradigm, they differ in assigning the stations to each day of the horizon. The resulting daily routing problems are then solved exactly until achieving optimalization. Moreover, an improvement procedure is also developed with the aim of ensuring a better quality solution. Our heuristics are tested and compared in two real-life cases, and our computational results show encouraging improvements with respect to a human planning solution
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6

Gonzalez-Holland, Emily, Daphne Whitmer, Larry Moralez, and Mustapha Mouloua. "Examination of the Use of Nielsen’s 10 Usability Heuristics & Outlooks for the Future." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1472–75. http://dx.doi.org/10.1177/1541931213601853.

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Анотація:
Heuristics are commonly employed throughout various stages of the design process to evaluate the usability of interfaces. Heuristic Evaluation (HE) provides researchers with a cost effective and practical means to effectively assess designs. In this article, we aim to outline the development and application of one of the most frequently cited set of heuristic evaluation tools, Nielsen’s (1994) 10 usability heuristics. Nielsen’s heuristics have not only been applied to various modalities of interface design, but have also been compared to other usability evaluation methods. Moreover, in many cases they have been modified so that they can be applied in an ever-changing socio-technical environment. In reviewing these developments, we propose theoretical and practical implications of these heuristic methods and present an outlook for the future. We argue that with the rapid expansion and growth of technology in the last 20 years, Nielsen’s 10 usability heuristics may need an update to remain consistent with modern usability problems.
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7

CHANG, KAI H., JAMES H. CROSS II, W. HOMER CARLISLE, and SHIH-SUNG LIAO. "A PERFORMANCE EVALUATION OF HEURISTICS-BASED TEST CASE GENERATION METHODS FOR SOFTWARE BRANCH COVERAGE." International Journal of Software Engineering and Knowledge Engineering 06, no. 04 (December 1996): 585–608. http://dx.doi.org/10.1142/s0218194096000247.

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Анотація:
Software testing is an important step in the development of complex systems. The construction of test cases using traditional methods usually requires considerable manual effort. QUEST/Ada—Query Utility Environment for Software Testing of Ada, is a prototype test case generation system that uses various heuristics-based approaches to generate test cases. The system, which is designed for unit testing, generates test cases by monitoring the branch coverage progress and intelligently modifying existing test cases to achieve additional coverage. Three heuristics-based approaches along with a random test case generation method were studied to compare their branch coverage performance. Although some constraints are imposed by the prototype, the framework provides a useful foundation for further heuristics-based test case generation research. The design of the system, the heuristic rules used in the system, and an evaluation of each rule’s performance are presented.
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8

Парфентьєва І. П. та Матвійчук К. О. "ЕТИМОЛОГІЯ ПОНЯТТЯ “ЕВРИСТИЧНИЙ ПІДХІД”". World Science 3, № 8(36) (30 серпня 2018): 46–49. http://dx.doi.org/10.31435/rsglobal_ws/30082018/6078.

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The article deals with the term "heuristics", which in scientific knowledge has the designation as a "method of finding." The author conducts an analysis of scientific literature on the interpretation of heuristics as a scientific concept. Heuristics as an independent science has not been fully formed yet. Despite the large number of scientific papers devoted to questions of heuristics, they usually relate to its particular problems and do not give a clear idea of either the object or subject of heuristics or its status among other sciences. It is suggested that pedagogical heuristics are defined as one of the branches of heuristics, which studies fundamental principles of didactics and the systematic organization of students' heuristic activity in a supervised interaction of a teacher and implements them in general and in vocational education using the system of problem tasks for the purposeful development of intelligence. The main tasks of pedagogical heuristics interact with the tasks of didactics in the qualitative formation of a future specialist. Therefore, pedagogical heuristics in researches use heuristic methods that allow to accelerate the process of solving any problem.
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9

Soria-Alcaraz, Jorge A., Gabriela Ochoa, Andres Espinal, Marco A. Sotelo-Figueroa, Manuel Ornelas-Rodriguez, and Horacio Rostro-Gonzalez. "A Methodology for Classifying Search Operators as Intensification or Diversification Heuristics." Complexity 2020 (February 13, 2020): 1–10. http://dx.doi.org/10.1155/2020/2871835.

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Анотація:
Selection hyper-heuristics are generic search tools that dynamically choose, from a given pool, the most promising operator (low-level heuristic) to apply at each iteration of the search process. The performance of these methods depends on the quality of the heuristic pool. Two types of heuristics can be part of the pool: diversification heuristics, which help to escape from local optima, and intensification heuristics, which effectively exploit promising regions in the vicinity of good solutions. An effective search strategy needs a balance between these two strategies. However, it is not straightforward to categorize an operator as intensification or diversification heuristic on complex domains. Therefore, we propose an automated methodology to do this classification. This brings methodological rigor to the configuration of an iterated local search hyper-heuristic featuring diversification and intensification stages. The methodology considers the empirical ranking of the heuristics based on an estimation of their capacity to either diversify or intensify the search. We incorporate the proposed approach into a state-of-the-art hyper-heuristic solving two domains: course timetabling and vehicle routing. Our results indicate improved performance, including new best-known solutions for the course timetabling problem.
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10

West, Todd, John Sessions, and Bogdan M. Strimbu. "Heuristic Optimization of Thinning Individual Douglas-Fir." Forests 12, no. 3 (February 28, 2021): 280. http://dx.doi.org/10.3390/f12030280.

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Анотація:
Research Highlights: (1) Optimizing mid-rotation thinning increased modeled land expectation values by as much as 5.1–10.1% over a representative reference prescription on plots planted at 2.7 and 3.7 m square spacings. (2) Eight heuristics, five of which were newly applied to selecting individual trees for thinning, produced thinning prescriptions of near identical quality. (3) Based on heuristic sampling properties, we introduced a variant of the hero heuristic with a 5.3–20% greater computational efficiency. Background and Objectives: Thinning, which is arguably the most subjective human intervention in the life of a stand, is commonly executed with limited decision support in tree selection. This study evaluated heuristics’ ability to support tree selection in a factorial experiment that considered the thinning method, tree density, thinning age, and rotation length. Materials and Methods: The Organon growth model was used for the financial optimization of even age Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) harvest rotations consisting of a single thinning followed by clearcutting on a high-productivity site. We evaluated two versions of the hero heuristic, four Monte Carlo heuristics (simulated annealing, record-to-record travel, threshold accepting, and great deluge), a genetic algorithm, and tabu search for their efficiency in maximizing land expectation value. Results: With 50–75 years rotations and a 4% discount rate, heuristic tree selection always increased land expectation values over other thinning methods. The two hero heuristics were the most computationally efficient methods. The four Monte Carlo heuristics required 2.8–3.4 times more computation than hero. The genetic algorithm and the tabu search required 4.2–8.4 and 21–52 times, respectively, more computation than hero. Conclusions: The accuracy of the resulting thinning prescriptions was limited by the quality of stand measurement, and the accuracy of the growth and yield models was linked to the heuristics rather than to the choice of heuristic. However, heuristic performance may be sensitive to the chosen models.
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Більше джерел

Дисертації з теми "Heuristics methods"

1

PINHEIRO, SAULO BORGES. "CONTAINERS ROAD TRANSPORTATION OPTIMIZATION: EXACT AND HEURISTICS METHODS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2013. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=34991@1.

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Apesar da dimensão continental brasileira, da grandeza de sua costa e da proximidade entre o litoral e os grandes centros urbanos, o transporte de cargas em contêineres utilizando a cabotagem ainda é muito restrito no Brasil. Neste cenário, para ganhar espaço, os armadores brasileiros de cabotagem buscam oferecer serviços porta-a-porta, conseguindo economias de escala na contratação dos fornecedores que realizam as pontas rodoviárias, aumentando assim a competitividade da cabotagem com seu principal concorrente, o modal rodoviário. Neste trabalho são apresentados dois modelos que visam minimizar o custo total de contratação de fornecedores rodoviários para uma lista de demandas que devem ser atendidas. O primeiro é um modelo matemático de programação linear inteira, o segundo é um algoritmo que utiliza uma heurística gulosa. Os modelos foram desenvolvidos e testados em cenários reais, vividos por armador de cabotagem brasileiro durante um período de tempo determinado. Os resultados dos dois modelos, que são comparados entre si e com as soluções realizadas manualmente por funcionários do armador de cabotagem, mostram que as soluções dos modelos de otimização são muito melhores do que as soluções manuais. Os resultados mostram ainda que o algoritmo guloso alcança resultados muito próximos aos do método exato, mostrando ser de grande utilidade dada a facilidade de sua implantação.
Despite the Brazilian continental scale, the magnitude of its coastline and the proximity between the coast and the large urban centers, the transport of cargo in containers using cabotage is still very limited in Brazil. In this scenario, the Brazilian cabotage ship-owners seek to provide door-to-door services, achieving economies of scale in procurement for suppliers that perform road ends, thus increasing the competitiveness of cabotage with its main competitor, the transportation by trucks. This work presents two models that aim to minimize the total cost of hiring road suppliers to a list of demands that must be performed. The first is a mathematical model based on integer linear programming, the second is an algorithm that uses a greedy heuristic. The models were developed and tested in real scenarios, experienced by a Brazilian cabotage ship-owner for a period of time. The results of the two models, which are compared among each other and with the manually solutions performed by the company’s employees, show that the solutions of optimization models are much better than the manual solutions. The results also show that the greedy algorithm achieves very close results to the exact method, proving to be very useful given the ease of its implementation.
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2

Panthulu, Pradeep. "Intelligent Memory Management Heuristics." Thesis, University of North Texas, 2003. https://digital.library.unt.edu/ark:/67531/metadc4399/.

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Анотація:
Automatic memory management is crucial in implementation of runtime systems even though it induces a significant computational overhead. In this thesis I explore the use of statistical properties of the directed graph describing the set of live data to decide between garbage collection and heap expansion in a memory management algorithm combining the dynamic array represented heaps with a mark and sweep garbage collector to enhance its performance. The sampling method predicting the density and the distribution of useful data is implemented as a partial marking algorithm. The algorithm randomly marks the nodes of the directed graph representing the live data at different depths with a variable probability factor p. Using the information gathered by the partial marking algorithm in the current step and the knowledge gathered in the previous iterations, the proposed empirical formula predicts with reasonable accuracy the density of live nodes on the heap, to decide between garbage collection and heap expansion. The resulting heuristics are tested empirically and shown to improve overall execution performance significantly in the context of the Jinni Prolog compiler's runtime system.
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3

Floriani, Lauro. "Multivariate statistical methods for studying the mechanics of heuristics." Nice, 2002. http://www.theses.fr/2002NICE5705.

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Анотація:
Les algorithmes constituent la plus efficace base de connaissances conçue par l'homme jusqu'à présent. La NP-completude indique que parmi l'ensemble des problèmes décidables il y en a que nous ne savons pas traiter de manière efficace, c. -à-d. Nous ne savons pas concevoir des algorithmes efficaces pour eux. Cependant, la pratique montre que beaucoup d'algorithmes sont quand même efficaces pour résoudre ces problèmes. C'est à dire que l'analyse expérimentale de leur relation entrée/sortie révèle une bien meilleure situation que ce qui peut être déduit d'une analyse mathématique des propriétés de ces algorithmes. Cela signifie également que le processus dynamique induit par l'algorithme (i. E. Le processus informatique) dépasse notre capacité d'expression et de communication du savoir que nous incluons dans un tel algorithme. Sans la mise en oeuvre effective de l'algorithme, nous ne serions pas capables de prédire son comportement de manière juste. Le travail de cette thèse concerne de tels processus dynamiques. Plutôt que d'analyser la connaissance que nous introduisons dans un algorithme, nous voulons étudier les mécanismes de ce processus informatique afin de déduire la connaissance qu'il contient. C'est ce que nous appelons "études exploratoires" car nous voulons acquérir de nouvelles connaissances sur le traitement du problème fourni par notre algorithme. Nous abordons ce sujet dans une perspective d'analyse de données. Notre méthode consiste à analyser le processus informatique dans sa recherche de tendances statistiques tangibles quant a sa mécanique. Afin de garantir l'aspect tangible de ces tendances, il est essentiel qu'elles rendent compte d'un processus informatique pertinent, c'est à dire reposant sur un grand nombre de données. L'analyse des données est donc un point crucial dans ce type d'études. Dans ce travail, nous présentons une application systématique des techniques statistiques d'analyse descriptive afin de mettre en évidence statistiquement les mécanismes des processus informatiques induits par les algorithmes heuristiques pour les problèmes d'optimisation difficiles. Nous présentons une étude de cas sur une heuristique à l'état de l'art sur le problème du voyageur de commerce dans laquelle nous interprétons et discutons les tendances mises en évidence par notre étude. La motivation pratique sous jacente à ce travail est l'optimisation dans le cadre du design des réseaux radio mobiles. Un contexte si particulier pose de lourdes contraintes quant a l'analyse des algorithmes, même par des expérimentations traditionnelles
Algorithms are the most effective knowledge repositories yet conceived by mankind for they automate computations on a given formal medium, the computer system. NP-Completeness tell us that among the computable treatable problems there are some which we do not know an efficient way of dealing with, i. E. We do not know how to conceive efficient algorithms for them. Nevertheless, practical experience tells us that many algorithms for these problems are indeed quite effective. That is to say that the experimental analysis of their input/output relationship reveal a far better situation than what can be derived by the mathematical analysis of these algorithms' properties. It also means that the dynamic process induced by the algorithm (i. E. The computational process) exceeds our capacity of express and communicate the knowledge we embed in such algorithm. Without the actual implementation of the algorithm we would not be able to tell their behavior. The work in this thesis concerns such dynamic process. Rather than analyze the properties of the knowledge we represent on an algorithm, we want to investigate the mechanics of the computational process in order to infer the knowledge behind it. That is what we call exploratory studies, for we want to acquire new knowledge about the treatment given by our algorithm to the problem. We approach this matter by a data analysis perspective. Our method consists on probing the computational process in search for insightful statistical evidences about its mechanics. In order to guarantee the insightful aspect of these evidences it is essential that they report on a pertinent computational process, i. E. For large input problems. Data analysis is therefore a crucial issue in such kind of study. In this work we present a systematic application of Multivariate Descriptive Statistical Analysis techniques to raise statistical evidences on the mechanics of the computational process induced by heuristic algorithms for hard optimization problems. We present a case study of a state of the art heuristic for the Traveling Salesman Problem where we interpret and discuss the evidences raised by our studies, showing their ability to provide us new knowledge about the heuristic. The practical motivation behind this work is the optimization context defined by the design of wireless telecommunications networks. Such a peculiar context poses severe constraints to the analysis of algorithms even by traditional experimentation
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4

Amir-Hussin, Amir A. B. "Heuristic methods for coalition structure generation." Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/26275.

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Анотація:
The Coalition Structure Generation (CSG) problem requires finding an optimal partition of a set of n agents. An optimal partition means one that maximizes global welfare. Computing an optimal coalition structure is computationally hard especially when there are externalities, i.e., when the worth of a coalition is dependent on the organisation of agents outside the coalition. A number of algorithms were previously proposed to solve the CSG problem but most of these methods were designed for systems without externalities. Very little attention has been paid to finding optimal coalition structures in the presence of externalities, although externalities are a key feature of many real world multiagent systems. Moreover, the existing methods, being non-heuristic, have exponential time complexity which means that they are infeasible for any but systems comprised of a small number of agents. The aim of this research is to develop effective heuristic methods for finding optimal coalition structures in systems with externalities, where time taken to find a solution is more important than the quality of the solution. To this end, four different heuristics methods namely tabu search, simulated annealing, ant colony search and particle swarm optimisation are explored. In particular, neighbourhood operators were devised for the effective exploration of the search space and a compact representation method was formulated for storing details about the multiagent system. Using these, the heuristic methods were devised and their performance was evaluated extensively for a wide range of input data.
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5

Remde, Stephen Mark. "Enhancing the performance of search heuristics : variable fitness functions and other methods to enhance heuristics for dynamic workforce scheduling." Thesis, University of Bradford, 2009. http://hdl.handle.net/10454/4310.

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Анотація:
Scheduling large real world problems is a complex process and finding high quality solutions is not a trivial task. In cooperation with Trimble MRM Ltd., who provide scheduling solutions for many large companies, a problem is identified and modelled. It is a general model which encapsulates several important scheduling, routing and resource allocation problems in literature. Many of the state-of-the-art heuristics for solve scheduling problems and indeed other problems require specialised heuristics tailored for the problem they are to solve. While these provide good solutions a lot of expert time is needed to study the problem, and implement solutions. This research investigates methods to enhance existing search based methods. We study hyperheuristic techniques as a general search based heuristic. Hyperheuristics raise the generality of the solution method by using a set of tools (low level heuristics) to work on the solution. These tools are problem specific and usually make small changes to the problem. It is the task of the hyperheuristic to determine which tool to use and when. Low level heuristics using exact/heuristic hybrid method are used in this thesis along with a new Tabu based hyperheuristic which decreases the amount of CPU time required to produce good quality solutions. We also develop and investigate the Variable Fitness Function approach, which provides a new way of enhancing most search-based heuristics in terms of solution quality. If a fitness function is pushing hard in a certain direction, a heuristic may ultimately fail because it cannot escape local minima. The Variable Fitness Function allows the fitness function to change over the search and use objective measures not used in the fitness calculation. The Variable Fitness Function and its ability to generalise are extensively tested in this thesis. The two aims of the thesis are achieved and the methods are analysed in depth. General conclusions and areas of future work are also identified.
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6

Remde, Stephen M. "Enhancing the Performance of Search Heuristics. Variable Fitness Functions and other Methods to Enhance Heuristics for Dynamic Workforce Scheduling." Thesis, University of Bradford, 2009. http://hdl.handle.net/10454/4310.

Повний текст джерела
Анотація:
Scheduling large real world problems is a complex process and finding high quality solutions is not a trivial task. In cooperation with Trimble MRM Ltd., who provide scheduling solutions for many large companies, a problem is identified and modelled. It is a general model which encapsulates several important scheduling, routing and resource allocation problems in literature. Many of the state-of-the-art heuristics for solve scheduling problems and indeed other problems require specialised heuristics tailored for the problem they are to solve. While these provide good solutions a lot of expert time is needed to study the problem, and implement solutions. This research investigates methods to enhance existing search based methods. We study hyperheuristic techniques as a general search based heuristic. Hyperheuristics raise the generality of the solution method by using a set of tools (low level heuristics) to work on the solution. These tools are problem specific and usually make small changes to the problem. It is the task of the hyperheuristic to determine which tool to use and when. Low level heuristics using exact/heuristic hybrid method are used in this thesis along with a new Tabu based hyperheuristic which decreases the amount of CPU time required to produce good quality solutions. We also develop and investigate the Variable Fitness Function approach, which provides a new way of enhancing most search-based heuristics in terms of solution quality. If a fitness function is pushing hard in a certain direction, a heuristic may ultimately fail because it cannot escape local minima. The Variable Fitness Function allows the fitness function to change over the search and use objective measures not used in the fitness calculation. The Variable Fitness Function and its ability to generalise are extensively tested in this thesis. The two aims of the thesis are achieved and the methods are analysed in depth. General conclusions and areas of future work are also identified.
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7

Kim, Dong-Gook. "An Analysis of Ecological and Social Rationality: When are Lexicographic Heuristics Preferred?" unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-08182008-212550/.

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Анотація:
Thesis (Ph. D.)--Georgia State University, 2008.
Title from file title page. Thomas Whalen, committee chair; Julian Diaz III, C. S. Thachenkary, Rodney Schultz, committee members. Electronic text (168 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed November 3, 2008. Includes bibliographical references (p. 164-168).
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8

Machac, Mary Kristin. "A Model of Expert Instructional Design Heuristics Incorporating Design Thinking Methods." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/102926.

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Novice instructional designers have limited experience working with ill-structured problems, and often do not possess the mental models to effectively analyze, manage, and communicate the overall design process of new instructional design projects (Wedman and Tessmer, 1993; Rowland, 1992; Perez and Emery, 1995; Liu, Gibby, Quiros, and Demps, 2002). In their 2016 article of expert instructional design principles applied by experienced designers in practice, York and Ertmer proposed the following questions for future research, "(a) Can we teach principles to novice instructional designers? (b) What methods should we use to provide this information?" (York and Ertmer, 2016, p. 189). This research further explored these questions and offers a new model of expert instructional design heuristics incorporating design thinking methods. The purpose of this study was to identify design thinking methods that aligned with heuristics of expert instructional design practitioners, and to design and develop a new model of heuristics and design thinking methods, which could assist novice instructional designers as they enter the instructional design field. The literature outlines challenges reported among novice instructional designers throughout the instructional design process, which includes their ability to solve ill-structured problems; conduct thorough analyses; collaborate in teams; negotiate priorities; generate a variety of ideas for solutions; overcome resource, budget and time constraints; communicate and manage projects with stakeholders; and prototype, iterate and pilot new design solutions (Rowland, 1992; Hoard, Stefaniak, Baaki, and Draper, 2019; Roytek, 2010; Liu, Gibby, Quiros, and Demps, 2002; Chang and Kuwata, 2020; Tracey and Boling, 2014; Perez and Emery, 1995; Williams van Rooij, 1993). The model offers novice instructional designers specific methods and combinations of methods to use for every stage of the instructional design process. As instructional designers implement design thinking methods within the context of their daily situations, they should become more comfortable and begin to adapt the methods to meet their individual needs for each stage of their process.
Doctor of Philosophy
Instructional design is a system of procedures for developing education and training curricula in a consistent and reliable fashion (Branch and Merrill, 2011; Branch and Kopcha, 2014). It embodies an iterative process for outlining outcomes, selecting teaching and learning strategies, choosing support technologies, identifying media, and measuring performance (Branch and Kopcha, 2014). Instructional designers use models of instructional design and instructional development to communicate tasks and procedures of the instructional design process (Andrews and Goodson, 1980). Over the years, numerous models of instructional design have been developed and adapted to meet the varying needs of instructional designers and developers. There is a consensus that most instructional processes consist of five core elements or stages: analysis, design, development, implementation, and evaluation, which are commonly referred to as ADDIE (Seels and Glasgow, 1990; Branch and Kopcha, 2014). While often considered generic, the ADDIE framework contains a useful set of common criteria, which most designers state as important or necessary as a part of any instructional design process (Pittenger, Janke, and Bumgardner, 2009; York and Ertmer, 2011; 2016). Novice instructional designers have limited experience working with ill-structured problems, and often do not possess the mental models (prior experience) to effectively analyze, manage, and communicate the overall design process of new instructional design projects (Wedman and Tessmer, 1993; Rowland, 1992; Perez and Emery, 1995; Liu, Gibby, Quiros, and Demps, 2002). In their 2016 article of expert instructional design principles applied by experienced designers in practice, York and Ertmer proposed the following questions for future research, "(a) Can we teach principles to novice instructional designers? (b) What methods should we use to provide this information?" (York and Ertmer, 2016, p. 189). This research further explored these questions and offers a new model of expert instructional design heuristics incorporating design thinking methods. For this study, heuristics were defined as generalized stages of an instructional designer's process and design thinking was defined as a human-centered design process for solving complex problems. The purpose of this study was to identify design thinking methods that aligned with heuristics of expert instructional design practitioners, and to design and develop a new model of heuristics and design thinking methods, which could assist novice instructional designers as they enter the instructional design field. The literature outlines challenges reported among novice instructional designers throughout the instructional design process, which includes their ability to solve ill-structured problems; conduct thorough analyses; collaborate in teams; negotiate priorities; generate a variety of ideas for solutions; overcome resource, budget and time constraints; communicate and manage projects with stakeholders; and prototype, iterate and pilot new design solutions (Rowland, 1992; Hoard, Stefaniak, Baaki, and Draper, 2019; Roytek, 2010; Liu, Gibby, Quiros, and Demps, 2002; Chang and Kuwata, 2020; Tracey and Boling, 2014; Perez and Emery, 1995; Williams van Rooij, 1993). The model offers novice instructional designers specific methods and combinations of methods to use for every stage of the instructional design process. As instructional designers implement design thinking methods within the context of their daily situations, they should become more comfortable and begin to adapt the methods to meet their individual needs for each stage of their process.
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9

Ozdemir, Ersin. "Evolutionary methods for the design of digital electronic circuits and systems." Thesis, Cardiff University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326874.

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10

Sucu, Seda. "Solving crew scheduling problem in offshore supply vessels : heuristics and decomposition methods." Thesis, University of Strathclyde, 2017. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=29270.

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For the efficient utilisation of resources in various transportation settings, scheduling is a significant area of research. Having crew as the main resource for operation maintenance, scheduling crew have been a powerful decision making tool for optimisation studies. This research provides a detailed real case study analysis regarding the difficulties in planning crew in maritime industry. As a special case study, this thesis researches crew scheduling in offshore supply vessels which are used for specific operations of a global scaled company in oil and gas industry deeply with modified formulations, heuristics and decomposition methods. An extended version of computational study for a simple formulation approach (Task Based Model) is applied as deeper analysis to Leggate (2016). Afterwards, more realistic approach to the same problem is revised. Following the revision, a customized and thorough computational study on the heuristic method with various settings is designed and implemented in C++. After elaborated analysis completed on the suggested models firstly, a modification on Time Windows model is presented to increase the efficacy. This modification provides a sharp decrease in upper bounds within a short time compared to the previously suggested models. Through this suggestion, more economic schedules within a short period of time are generated. Achieving high performances from the modified model, an application of a decomposition algorithm is provided. We implemented a hybrid solution of Benders Decomposition with a customized heuristic for the modified model. Although this hybrid solution does not provide high quality solutions, it evaluates the performance of possible decomposed models with potential improvements for future research. An introduction to robust crew scheduling in maritime context is also given with a description of resources of uncertainty in this concept and initial robust formulations are suggested.
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Книги з теми "Heuristics methods"

1

Rabadi, Ghaith, ed. Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26024-2.

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2

Lewis, John N. Expert systems development utilizing heuristic methods. Monterey, Calif: Naval Postgraduate School, 1996.

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3

Martí, Rafael, and Gerhard Reinelt. Exact and Heuristic Methods in Combinatorial Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-64877-3.

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4

Eggen, Loren G. Approximating the chromatic number of an arbitrary graph using a supergraph heuristic. Monterey, Calif: Naval Postgraduate School, 1997.

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5

Mahtani, Pravesh. Heuristic methods for backup lightpath routing in WDM networks. Ottawa: National Library of Canada, 2001.

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6

Roos, N. TUD Faculty of Technical Mathematics and Informatics: Heuristic reasoning. Amsterdam, Netherlands: National Aerospace Laboratory, 1988.

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7

Nicol, David M. A multistage linear array assignment problem. Hampton, Va: ICASE, 1988.

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8

Nagy, Gabor. Heuristic methods for the many-to-many location-routing problem. Birmingham: University of Birmingham, 1996.

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9

Lebak, James M. Toward a portable parallel library for space-time adaptive methods. Ithaca, N.Y: Cornell Theory Center, Cornell University, 1996.

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10

Gerhard, Reinelt, and SpringerLink (Online service), eds. The Linear Ordering Problem: Exact and Heuristic Methods in Combinatorial Optimization. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Частини книг з теми "Heuristics methods"

1

Li, PhD, Haksun. "Heuristics." In Numerical Methods Using Java, 625–54. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-6797-4_11.

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2

Martí, Rafael, Jose A. Lozano, Alexander Mendiburu, and Leticia Hernando. "Multi-start Methods." In Handbook of Heuristics, 155–75. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-07124-4_1.

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3

Parsopoulos, Konstantinos E. "Particle Swarm Methods." In Handbook of Heuristics, 639–85. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-07124-4_22.

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Martí, Rafael, Jose A. Lozano, Alexander Mendiburu, and Leticia Hernando. "Multi-start Methods." In Handbook of Heuristics, 1–21. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-07153-4_1-1.

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Parsopoulos, Konstantinos E. "Particle Swarm Methods." In Handbook of Heuristics, 1–47. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-07153-4_22-1.

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6

Martí, Rafael, and Gerhard Reinelt. "Meta-Heuristics." In Exact and Heuristic Methods in Combinatorial Optimization, 59–123. Berlin, Heidelberg: Springer Berlin Heidelberg, 2022. http://dx.doi.org/10.1007/978-3-662-64877-3_3.

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7

Wright, Mike B., and Richard C. Marett. "A Preliminary Investigation into the Performance of Heuristic Search Methods Applied to Compound Combinatorial Problems." In Meta-Heuristics, 299–317. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1361-8_19.

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Lowndes, Val, Ovidiu Bagdasar, and Stuart Berry. "Case Studies: Using Heuristics." In Simulation Foundations, Methods and Applications, 175–97. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55417-4_6.

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9

Michalewicz, Zbigniew, and David B. Fogel. "Traditional Methods — Part 1." In How to Solve It: Modern Heuristics, 55–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-07807-5_4.

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Michalewicz, Zbigniew, and David B. Fogel. "Traditional Methods — Part 2." In How to Solve It: Modern Heuristics, 87–109. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-07807-5_5.

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Тези доповідей конференцій з теми "Heuristics methods"

1

"Multiple RNA Interaction - Formulations, Approximations, and Heuristics." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004341402420249.

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2

Hu, Shuli, and Nathan R. Sturtevant. "Direction-Optimizing Breadth-First Search with External Memory Storage." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/175.

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While computing resources have continued to grow, methods for building and using large heuristics have not seen significant advances in recent years. We have observed that direction-optimizing breadth-first search, developed for and used broadly in the Graph 500 competition, can also be applied for building heuristics. But, the algorithm cannot run efficiently using external memory -- when the heuristics being built are larger than RAM. This paper shows how to modify direction-optimizing breadth-first search to build external-memory heuristics. We show that the new approach is not effective in state spaces with low asymptotic branching factors, but in other domains we are able to achieve up to a 3x reducing in runtime when building an external-memory heuristic. The approach is then used to build a 2.6TiB Rubik's Cube heuristic with 5.8 trillion entries, the largest pattern database heuristic ever built.
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3

Berzish, Murphy, Vijay Ganesh, and Yunhui Zheng. "Z3str3: A String Solver with Theory-aware Heuristics." In 2017 Formal Methods in Computer-Aided Design (FMCAD). IEEE, 2017. http://dx.doi.org/10.23919/fmcad.2017.8102241.

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4

De Filippo, Allegra, Michele Lombardi, and Michela Milano. "Methods for off-line/on-line optimization under uncertainty." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/177.

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In this work we present two general techniques to deal with multi-stage optimization problems under uncertainty, featuring off-line and on-line decisions. The methods are applicable when: 1) the uncertainty is exogenous; 2) there exists a heuristic for the on-line phase that can be modeled as a parametric convex optimization problem. The first technique replaces the on-line heuristics with an anticipatory solver, obtained through a systematic procedure. The second technique consists in making the off-line solver aware of the on-line heuristic, and capable of controlling its parameters so as to steer its behavior. We instantiate our approaches on two case studies: an energy management system with uncertain renewable generation and load demand, and a vehicle routing problem with uncertain travel times. We show how both techniques achieve high solution quality w.r.t. an oracle operating under perfect information, by obtaining different trade-offs in terms of computation time.
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Tromp, Nynke, Reint Jan Renes, and Jaap Daalhuizen. "Heuristics for selecting and using behavioural design methods." In Design Research Society Conference 2018. Design Research Society, 2018. http://dx.doi.org/10.21606/drs.2018.607.

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6

Kureychik, Viktor, Vladimir Kureychik, Liliya Kureychik, and Roman Potarusov. "Heuristics methods for solving the block packing problem." In Information Technologies in Science, Management, Social Sphere and Medicine. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/itsmssm-16.2016.62.

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7

Gross, Ari D. "Shape from contour methods using object-based heuristics." In Applications in Optical Science and Engineering, edited by Robert A. Melter and Angela Y. Wu. SPIE, 1993. http://dx.doi.org/10.1117/12.142170.

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8

Tuisov, Alexander, and Michael Katz. "The Fewer the Merrier: Pruning Preferred Operators with Novelty." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/576.

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Heuristic search is among the best performing approaches to classical satisficing planning, with its performance heavily relying on informative and fast heuristics, as well as search-boosting and pruning techniques. While both heuristics and pruning techniques have gained much attention recently, search-boosting techniques in general, and preferred operators in particular have received less attention in the last decade. Our work aims at bringing the light back to preferred operators research, with the introduction of preferred operators pruning technique, based on the concept of novelty. Continuing the research on novelty with respect to an underlying heuristic, we present the definition of preferred operators for such novelty heuristics. For that, we extend the previously defined concepts to operators, allowing us to reason about the novelty of the preferred operators. Our experimental evaluation shows the practical benefit of our suggested approach, compared to the currently used methods.
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Tkachuk, Anton, and Mykola Tkachuk. "DISPERSION DESIGN OF 1D PERIODIC DISCRETE SYSTEMS USING LOG-DET HEURISTICS." In 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering Methods in Structural Dynamics and Earthquake Engineering. Athens: Institute of Structural Analysis and Antiseismic Research National Technical University of Athens, 2021. http://dx.doi.org/10.7712/120121.8611.18609.

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10

De Rango, F., A. F. Santamaria, M. Tropea, and S. Marano. "Meta-Heuristics Methods for a NP-Complete Networking Problem." In 2008 IEEE 68th Vehicular Technology Conference (VTC 2008-Fall). IEEE, 2008. http://dx.doi.org/10.1109/vetecf.2008.279.

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Звіти організацій з теми "Heuristics methods"

1

Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, May 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.
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Rotemberg, Julio. A Heuristic Method for Extracting Smooth Trends from Economic Time Series. Cambridge, MA: National Bureau of Economic Research, December 1999. http://dx.doi.org/10.3386/w7439.

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3

Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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