<p><P>Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of METAHEURISTIC OPTIMIZATION VIA MEMORY AND EVOLUTION: Tabu Search and
Metaheuristic Optimization via Memory and Evolution. Tabu Search and Scatter Search
β Scribed by Cesar Rego, Bahram Alidaee
- Publisher
- Springer
- Year
- 2010
- Tongue
- English
- Leaves
- 471
- Series
- Operations Research Computer Science Interfaces Series
- Edition
- 1st Edition.
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.
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Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatte
<p><P>Metaheuristics for Hard Optimization comprises of three parts. The first part is devoted to the detailed presentation of the four most widely known metaheuristics:</P><P>β’ the simulated annealing method,</P><P>β’ tabu search,</P><P>β’ the evolutionary algorithms,</P><P>β’ ant colony algorithms.</
<p>This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emp