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A collection of papers surveying recent progress in the field of Combinatorial Optimization. Topics examined include theoretical and computational aspects (Boolean Programming, Probabilistic Analysis of Algorithms, Parallel Computer Models and Combinatorial Algorithms), well-known combinatorial problems (such as the Linear Assignment Problem, the Quadratic Assignment Problem, the Knapsack Problem and Steiner Problems in Graphs) and more applied problems (such as Network Synthesis and Dynamic Network Optimization, Single Facility Location Problems on Networks, the Vehicle Routing Problem and Scheduling Problems).
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This book is a collection of six articles arising from the meeting of the NATO Advanced Study Institute (ASI) ""Combinatorial Optimization: Methods and Applications,"" which was held at the University of Montreal in June 2006. This ASI consisted of seven series of five one-hour lectures and one series of four one-hour lectures. It was attended by some sixty students of graduate or postdoctoral level from fifteen countries worldwide. It includes topics such as: integer and mixed integer programming, facility location, branching on split disjunctions, convexity in combinatorial optimization, and
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Combinatorial optimization --- Mathematics --- Shoelaces --- Combinatorial optimization. --- Mathematics.
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This book presents recent advances in computational optimization. Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real-world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. The book is a comprehensive collection of extended contributions from the Workshops on Computational Optimization 2020. The book includes important real problems like modeling of physical processes, workforce planning, parameter settings for controlling different processes, transportation problems, wireless sensor networks, machine scheduling, air pollution modeling, solving multiple integrals and systems of differential equations which describe real processes, solving engineering problems. It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming and others. This research demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization problems.
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