Constraint Handling in Metaheuristics and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Constraint Handling in Metaheuristics and Applications write by Anand J. Kulkarni. This book was released on 2021-04-12. Constraint Handling in Metaheuristics and Applications available 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.
Constraint-based Local Search
Constraint-based Local Search - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Constraint-based Local Search write by Pascal Van Hentenryck. This book was released on 2005. Constraint-based Local Search available 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.
Constraint Handling in Cohort Intelligence Algorithm
Constraint Handling in Cohort Intelligence Algorithm - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Constraint Handling in Cohort Intelligence Algorithm write by Ishaan R. Kale. This book was released on 2021-12-26. Constraint Handling in Cohort Intelligence Algorithm available 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.
Meta-Heuristics
Meta-Heuristics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Meta-Heuristics write by Ibrahim H. Osman. This book was released on 2012-12-06. Meta-Heuristics available 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.
Constraint Handling Rules
Constraint Handling Rules - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Constraint Handling Rules write by Tom Schrijvers. This book was released on 2009-03-26. Constraint Handling Rules available 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.
