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Metaheuristics for Scheduling in Industrial and Manufacturing Applications, Fatos Xhafa; Ajith Abraham


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Автор: Fatos Xhafa; Ajith Abraham
Название:  Metaheuristics for Scheduling in Industrial and Manufacturing Applications
ISBN: 9783642097782
Издательство: Springer
Классификация: ISBN-10: 3642097782
Обложка/Формат: Paperback
Страницы: 369
Вес: 0.52 кг.
Дата издания: 2008
Серия: Studies in Computational Intelligence
Язык: English
Размер: 234 x 156 x 20
Читательская аудитория: Science
Ссылка на Издательство: Link
Поставляется из: Германии
Описание: During the past decades scheduling has been among the most studied op- mization problemsanditisstillanactiveareaofresearch Schedulingappears in many areas of science, engineering and industry and takes di?erent forms depending on the restrictions and optimization criteria of the operating en- ronments 8]. For instance, in optimization and computer science, scheduling has been de?ned as the allocation of tasks to resources over time in order to achieve optimality in one or more objective criteria in an e?cient way and in production as production schedule, i. e., the planning of the production or the sequence of operations according to which jobs pass through machines and is optimal with respect to certain optimization criteria. Although there is a standardized form of stating any scheduling problem, namely e?cient allocation ofn jobs onm machines -which can process no more than one activity at a time- with the objective to optimize some - jective function of the job completion times, scheduling is in fact a family of problems. Indeed, several parameters intervene in the problem de?nition: (a) job characteristics (preemptive or not, precedence constraints, release dates, etc. ); (b) resource environment (single vs. parallel machines, un- lated machines, identical or uniform machines, etc. ); (c) optimization criteria (minimize total tardiness, the number of late jobs, makespan, ?owtime, etc.; maximize resource utilization, etc. ); and, (d) scheduling environment (static vs. dynamic, intheformerthenumberofjobstobeconsideredandtheirready times are available while in the later the number of jobs and their charact- istics change over time).


Handbook of Metaheuristics

Автор: Gendreau
Название: Handbook of Metaheuristics
ISBN: 1441916636 ISBN-13(EAN): 9781441916631
Издательство: Springer
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Цена: 33401.00 р.
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Описание: Metaheuristics have grown into one of the most prominent areas of operations research. This update of a trailblazing volume examines the latest developments in the field.

Metaheuristics

Автор: Patrick Siarry
Название: Metaheuristics
ISBN: 3319454013 ISBN-13(EAN): 9783319454016
Издательство: Springer
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Цена: 19564.00 р.
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Описание: Introduction.- Simulated Annealing.- Tabu Search.- Search in Variable Neighborhoods.- The GRASP Search Algorithm.- Evolutionary Algorithms.- Artificial Ants.- Particle Swarms.- Other Metaheuristics.- Other Social Insect Algorithms.- Extending Evolutionary Algorithms for Multiobjective Optimization.- Extending Evolutionary Algorithms for Optimization Under Constraints.- Modeling and Comparison Methods.- Hybrid Metaheuristics for Optimizing Logistics.- Metaheuristics for Vehicle Routing Problems.- Applications in Air Traffic Management.

Tuning Metaheuristics

Автор: Mauro Birattari
Название: Tuning Metaheuristics
ISBN: 3642101496 ISBN-13(EAN): 9783642101496
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Metaheuristics are a relatively new but already established approachto c- binatorial optimization. A metaheuristic is a generic algorithmic template that can be used for ?nding high quality solutions of hard combinatorial - timization problems. To arrive at a functioning algorithm, a metaheuristic needs to be con?gured: typically some modules need to be instantiated and someparametersneedto betuned.Icallthese twoproblems"structural"and "parametric" tuning, respectively. More generally, I refer to the combination of the two problems as "tuning." Tuning is crucial to metaheuristic optimization both in academic research andforpracticalapplications.Nevertheless, relativelylittle researchhasbeen devoted to the issue. This book shows that the problem of tuning a me- heuristic can be described and solved as a machine learning problem. Using the machine learning perspective, it is possible to give a formal de?nitionofthetuningproblemandtodevelopagenericalgorithmfortuning metaheuristics.Moreover, fromthemachinelearningperspectiveitispossible tohighlightsome?awsinthecurrentresearchmethodologyandtostatesome guidelines for future empirical analysis in metaheuristics research. This book is based on my doctoral dissertation and contains results I have obtained starting from 2001 while working within the Metaheuristics Net- 1 work. During these years I have been a?liated with two research groups: INTELLEKTIK, Technische Universit t Darmstadt, Darmstadt, Germany and IRIDIA, Universit Libre de Bruxelles, Brussels, Belgium. I am the- fore grateful to the research directors of these two groups: Prof. Wolfgang Bibel, Dr. Thomas St tzle, Prof. Philippe Smets, Prof. Hugues Bersini, and Prof. Marco Dorigo.

Metaheuristics in Water, Geotechnical and Transport Engineering

Автор: Yang Xin-She, Gandomi Amir Hossein, Talatahari Siamak
Название: Metaheuristics in Water, Geotechnical and Transport Engineering
ISBN: 0323282601 ISBN-13(EAN): 9780323282604
Издательство: Elsevier Science
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Цена: 10273.00 р.
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Описание: Due to an ever-decreasing supply in raw materials and stringent constraints on conventional energy sources, demand for lightweight, efficient and low cost structures has become crucially important in modern engineering design. This requires engineers to search for optimal and robust design options to address design problems that are often large in scale and highly nonlinear, making finding solutions challenging. In the past two decades, metaheuristic algorithms have shown promising power, efficiency and versatility in solving these difficult optimization problems. . . This book examines the latest developments of metaheuristics and their applications in water, geotechnical and transport engineering offering practical case studies as examples to demonstrate real world applications. Topics cover a range of areas within engineering, including reviews of optimization algorithms, artificial intelligence, cuckoo search, genetic programming, neural networks, multivariate adaptive regression, swarm intelligence, genetic algorithms, ant colony optimization, evolutionary multiobjective optimization with diverse applications in engineering such as behavior of materials, geotechnical design, flood control, water distribution and signal networks. This book can serve as a supplementary text for design courses and computation in engineering as well as a reference for researchers and engineers in metaheursitics, optimization in civil engineering and computational intelligence.

Metaheuristics for Air Traffic Management

Автор: Durand
Название: Metaheuristics for Air Traffic Management
ISBN: 1848218109 ISBN-13(EAN): 9781848218109
Издательство: Wiley
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Цена: 22010.00 р.
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Описание: Air Traffic Management involves many different services such as Airspace Management, Air Traffic Flow Management and Air Traffic Control. Many optimization problems arise from these topics and they generally involve different kinds of variables, constraints, uncertainties. Metaheuristics are often good candidates to solve these problems.

Robust Control Optimization with Metaheuristics

Автор: Feyel
Название: Robust Control Optimization with Metaheuristics
ISBN: 1786300427 ISBN-13(EAN): 9781786300423
Издательство: Wiley
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Цена: 22010.00 р.
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Описание: In the automotive industry, a Control Engineer must design a unique control law that is then tested and validated on a single prototype with a level of reliability high enough to to meet a number of complex specifications on various systems.


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