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商品描述
Description:
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.
Pascal Van Hentenryck is Professor in the Department of Computer Science at Brown University. He is the author or editor of several previous MIT Press books, including Principles and Practice of Constraint Programming (1995).
Laurent Michel is Assistant Professor in the Department of Computer Science and Engineering at the University of Connecticut.
Table of Contents:
Preface xi I LOCAL SEARCH 1 Neighborhood Search 3 2 Heuristics and Mathematics 11 II CONSTRAINT-BASED LOCAL SEARCH 3 Constraint-Based Local Search 29 4 Modeling 43 5 Searching 57 III COMET 6 Invariants 85 7 Differentiable Objects 99 8 Control 139 9 First-Order Control 153 IV APPLICATIONS 10 Tabu Search 185 11 Variable Neighborhood Search 243 12 Simulated Annealing 251 13 Guided Local Search 267 14 Hybrid Evolutionary Search 285 15 Domain-Independent Local Search 295 16 Ant Colony Optimization 311 V SCHEDULING 17 Jobshop Scheduling 327 18 Scheduling Abstractions 337 19 Minimizing Total Tardiness in a Jobshop 345 20 Minimizing Makespan in a Jobshop 355 21 Minimizing Makespan in a Jobshop Again 377 22 Cumulative Scheduling 395 References 407 Index 417
商品描述(中文翻譯)
描述:
結合約束編程和局部搜索的方法用於解決組合優化問題,使用約束來描述和控制局部搜索,並使用COMET編程語言來支持建模和搜索抽象,以達到約束編程的高度抽象水平。本書首先概述了局部搜索的概念,包括鄰域、啟發式和元啟發式,然後介紹了基於約束的局部搜索的架構、建模和搜索組件,並描述了COMET中對基於約束的局部搜索的支持。書中還介紹了各種應用,按照元啟發式的方式進行排列。書中還包括一些滿足性問題,展示了基於約束的局部搜索方法在處理滿足性和優化問題時的統一能力。作者Pascal Van Hentenryck是布朗大學計算機科學系的教授,他是多本麻省理工學院出版社的書籍的作者或編輯,包括《約束編程的原理與實踐》(1995年)。作者Laurent Michel是康涅狄格大學計算機科學和工程系的助理教授。
目錄:
前言
第一部分 局部搜索
第1章 鄰域搜索
第2章 啟發式和數學
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