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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.
Mathematical optimization --- Operations research --- Operations research. --- Computer science. --- Operations Research/Decision Theory. --- Operations Research, Management Science. --- Math Applications in Computer Science. --- Informatics --- Science --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Decision making. --- Management science. --- Computer science—Mathematics. --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Quantitative business analysis --- Statistical decision --- Decision making --- Optimització matemàtica --- Investigació operativa. --- Investigació --- Assignació de recursos --- Mètodes de simulació --- Programació (Matemàtica) --- Teoria de cues --- Enginyeria de sistemes --- Jocs d'estratègia (Matemàtica) --- Optimització combinatòria --- Programació dinàmica --- Anàlisi de sistemes --- Computer science --- Operations Research and Decision Theory. --- Operations Research, Management Science . --- Mathematical Applications in Computer Science. --- Mathematics.
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Network analysis (Planning) --- Logistics. --- Military art and science --- Project networks --- Planning --- System analysis
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Combinatorial Optimization represents a major component of Operations Research, Mathematical Programming, and, in a broader sense, the development of digital intelligence (and society). It covers, in particular, such important areas as network design, location, routing, and scheduling, with major applications in transportation, logistics, health systems, production, communications, and energy. Starting from the exceptional contribution Professor Bernard Gendron made to combinatorial optimization and its applications in multiple areas, the book presents a state-of-the-art view on the field through a combination of surveys, expository articles, and focused methodological and applied research. The authors hail from various Operations Research areas and institutions around the world. Having collaborated closely with Professor Gendron, they drew on his foundational work to showcase a variety of models and algorithms that draw a living picture of the multifaceted word of applied combinatorial optimization.
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