Constraint Handling In Metaheuristics And Applications PDF Download
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| Author | : Anand J. Kulkarni |
| Publisher | : Springer Nature |
| Total Pages | : 315 |
| Release | : 2021-04-12 |
| Genre | : Computers |
| ISBN | : 9813367105 |
Download Constraint Handling in Metaheuristics and Applications Book in PDF, ePub and Kindle
This book aims to discuss the core and underlying principles and analysis of the different constraint handling approaches. The main emphasis of the book is on providing an enriched literature on mathematical modelling of the test as well as real-world problems with constraints, and further development of generalized constraint handling techniques. These techniques may be incorporated in suitable metaheuristics providing a solid optimized solution to the problems and applications being addressed. The book comprises original contributions with an aim to develop and discuss generalized constraint handling approaches/techniques for the metaheuristics and/or the applications being addressed. A variety of novel as well as modified and hybridized techniques have been discussed in the book. The conceptual as well as the mathematical level in all the chapters is well within the grasp of the scientists as well as the undergraduate and graduate students from the engineering and computer science streams. The reader is encouraged to have basic knowledge of probability and mathematical analysis and optimization. The book also provides critical review of the contemporary constraint handling approaches. The contributions of the book may further help to explore new avenues leading towards multidisciplinary research discussions. This book is a complete reference for engineers, scientists, and students studying/working in the optimization, artificial intelligence (AI), or computational intelligence arena.
| Author | : Ishaan R. Kale |
| Publisher | : CRC Press |
| Total Pages | : 206 |
| Release | : 2021-12-27 |
| Genre | : Business & Economics |
| ISBN | : 100052048X |
Download Constraint Handling in Cohort Intelligence Algorithm Book in PDF, ePub and Kindle
Mechanical Engineering domain problems are generally complex, consisting of different design variables and constraints. These problems may not be solved using gradient-based optimization techniques. The stochastic nature-inspired optimization techniques have been proposed in this book to efficiently handle the complex problems. The nature-inspired algorithms are classified as bio-inspired, swarm, and physics/chemical-based algorithms. Socio-inspired is one of the subdomains of bio-inspired algorithms, and Cohort Intelligence (CI) models the social tendencies of learning candidates with an inherent goal to achieve the best possible position. In this book, CI is investigated by solving ten discrete variable truss structural problems, eleven mixed variable design engineering problems, seventeen linear and nonlinear constrained test problems and two real-world applications from manufacturing domain. Static Penalty Function (SPF) is also adopted to handle the linear and nonlinear constraints, and limitations in CI and SPF approaches are examined. Constraint Handling in Cohort Intelligence Algorithm is a valuable reference to practitioners working in the industry as well as to students and researchers in the area of optimization methods.
| Author | : Pascal Van Hentenryck |
| Publisher | : MIT Press (MA) |
| Total Pages | : 456 |
| Release | : 2005 |
| Genre | : Computers |
| ISBN | : |
Download Constraint-based Local Search Book in PDF, ePub and Kindle
The ubiquity of combinatorial optimization problems in our society is illustrated by the novel application areas for optimization technology, which range from supply chain management to sports tournament scheduling. Over the last two decades, constraint programming has emerged as a fundamental methodology to solve a variety of combinatorial problems, and rich constraint programming languages have been developed for expressing and combining constraints and specifying search procedures at a high level of abstraction. Local search approaches to combinatorial optimization are able to isolate optimal or near-optimal solutions within reasonable time constraints. This book introduces a method for solving combinatorial optimization problems that combines constraint programming and local search, using constraints to describe and control local search, and a programming language, COMET, that supports both modeling and search abstractions in the spirit of constraint programming. After an overview of local search including neighborhoods, heuristics, and metaheuristics, the book presents the architecture and modeling and search components of constraint-based local search and describes how constraint-based local search is supported in COMET. The book describes a variety of applications, arranged by meta-heuristics. It presents scheduling applications, along with the background necessary to understand these challenging problems. The book also includes a number of satisfiability problems, illustrating the ability of constraint-based local search approaches to cope with both satisfiability and optimization problems in a uniform fashion.
| Author | : A. Kaveh |
| Publisher | : Springer |
| Total Pages | : 381 |
| Release | : 2016-11-30 |
| Genre | : Technology & Engineering |
| ISBN | : 331948012X |
Download Applications of Metaheuristic Optimization Algorithms in Civil Engineering Book in PDF, ePub and Kindle
The book presents recently developed efficient metaheuristic optimization algorithms and their applications for solving various optimization problems in civil engineering. The concepts can also be used for optimizing problems in mechanical and electrical engineering.
| Author | : Ibrahim H. Osman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 676 |
| Release | : 2012-12-06 |
| Genre | : Business & Economics |
| ISBN | : 1461313619 |
Download Meta-Heuristics Book in PDF, ePub and Kindle
Meta-heuristics have developed dramatically since their inception in the early 1980s. They have had widespread success in attacking a variety of practical and difficult combinatorial optimization problems. These families of approaches include, but are not limited to greedy random adaptive search procedures, genetic algorithms, problem-space search, neural networks, simulated annealing, tabu search, threshold algorithms, and their hybrids. They incorporate concepts based on biological evolution, intelligent problem solving, mathematical and physical sciences, nervous systems, and statistical mechanics. Since the 1980s, a great deal of effort has been invested in the field of combinatorial optimization theory in which heuristic algorithms have become an important area of research and applications. This volume is drawn from the first conference on Meta-Heuristics and contains 41 papers on the state-of-the-art in heuristic theory and applications. The book treats the following meta-heuristics and applications: Genetic Algorithms, Simulated Annealing, Tabu Search, Networks & Graphs, Scheduling and Control, TSP, and Vehicle Routing Problems. It represents research from the fields of Operations Research, Management Science, Artificial Intelligence and Computer Science.
| Author | : Michel Gendreau |
| Publisher | : Springer |
| Total Pages | : 611 |
| Release | : 2018-09-20 |
| Genre | : Business & Economics |
| ISBN | : 3319910868 |
Download Handbook of Metaheuristics Book in PDF, ePub and Kindle
The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book’s chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.
| Author | : Tom Schrijvers |
| Publisher | : Springer |
| Total Pages | : 252 |
| Release | : 2009-03-26 |
| Genre | : Computers |
| ISBN | : 3540922431 |
Download Constraint Handling Rules Book in PDF, ePub and Kindle
The ConstraintHandling Rules (CHR) languagecameto life morethan 15 years ago.Sincethen,ithasbecomeamajordeclarativespeci?cationandimplemen- tion language for constraint-based algorithms and applications. In recent years, the ?ve Workshops on Constraint Handling Rules have spurred the exchange of ideas within the CHR community, which has led to increased international collaboration, new theoretical results and optimized implementations. The aim of this volume of Lecture Notes in Ariti?cial Intelligence was to attract high-quality research papers on these recent advances in CHR. The 8 papersinthis issuewereselectedfrom11submissionsaftercarefulreviewingand subsequent revisions. Each paper was reviewd by three reviewers. The accepted papers represent some of the research teams on CHR around the world. It is not by accident that the currently most active research group is featured here with three articles. We also would have liked to see contributions from other CHR teams, but space is limited and the reviewers took their job seriously. After an introductory article that foreshadows an upcoming monograph on CHR, the accepted papers span a range of current research topics in the CHR community. It goes from extending the CHR language with search facilities and the related adaptive framework, and from generating rules from speci?cations of constraint solvers to implementing abductive probabilistic reasoning. They cover the theory that is a compositional semantics for CHR and ?nally describe e?cient implementations of CHR in traditional mainstream programming l- guages and compiler optimizations in the context of the re?ned semantics of CHR. Wewouldliketothanktheauthorsofsubmittedpapersandthemanyrevi- ers for their contribution in making this collection of research papers possible.
| Author | : Christian Blum |
| Publisher | : Springer |
| Total Pages | : 172 |
| Release | : 2016-05-23 |
| Genre | : Computers |
| ISBN | : 3319308831 |
Download Hybrid Metaheuristics Book in PDF, ePub and Kindle
This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives. The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.
| Author | : Seyedali Mirjalili |
| Publisher | : Elsevier |
| Total Pages | : 468 |
| Release | : 2023-01-31 |
| Genre | : Computers |
| ISBN | : 0323972675 |
Download Comprehensive Metaheuristics Book in PDF, ePub and Kindle
Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applications across a variety of research fields. The book starts with fundamentals, mathematical prerequisites, and conceptual approaches to provide readers with a solid foundation. After presenting multi-objective optimization, constrained optimization, and problem formation for metaheuristics, world-renowned authors give readers in-depth understanding of the full spectrum of algorithms and techniques. Scientists, researchers, academicians, and practitioners who are interested in optimizing a process or procedure to achieve a goal will benefit from the case studies of real-world applications from different domains. The book takes a much-needed holistic approach, putting the most widely used metaheuristic algorithms together with an in-depth treatise on multi-disciplinary applications of metaheuristics. Each algorithm is thoroughly analyzed to observe its behavior, providing a detailed tutorial on how to solve problems using metaheuristics. New case studies and research problem statements are also discussed, which will help researchers in their application of the concepts. Presented by world-renowned researchers and practitioners in metaheuristics Includes techniques, algorithms, and applications based on real-world case studies Presents the methodology for formulating optimization problems for metaheuristics Provides readers with methods for analyzing and tuning the performance of a metaheuristic, as well as for integrating metaheuristics in other AI techniques Features online complementary source code from the applications and algorithms
| Author | : Sara Lumbreras |
| Publisher | : Springer Nature |
| Total Pages | : 311 |
| Release | : 2020-11-19 |
| Genre | : Technology & Engineering |
| ISBN | : 3030494284 |
Download Transmission Expansion Planning: The Network Challenges of the Energy Transition Book in PDF, ePub and Kindle
This book presents a panoramic look at the transformation of the transmission network in the context of the energy transition. It provides readers with basic definitions as well as details on current challenges and emerging technologies. In-depth chapters cover the integration of renewables, the particularities of planning large-scale systems, efficient reduction and solution methods, the possibilities of HVDC and super grids, distributed generation, smart grids, demand response, and new regulatory schemes. The content is complemented with case studies that highlight the importance of the power transmission network as the backbone of modern energy systems. This book will be a comprehensive reference that will be useful to both academics and practitioners.
