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Frontiers in Computing Technologies for Manufacturing ApplicationsMetaheuristic Optimization in Certain and Uncertain Environments

Frontiers in Computing Technologies for Manufacturing Applications: Metaheuristic Optimization in... Metaheuristic Optimization in Certain and Uncertain Environments 2.1 Introduction Until now, a variety of optimization methods have been used as effective tools for making a rational decision in manufacturing systems and will surely continue to do so. By virtue of the outstanding progress in computers, many applications have been carried out in the real world using commercial software that has been developed greatly. To understand the proper usage of software and the adequate choice of optimization method through revealing merits and demerits compared with recent metaheuristic approaches, it is essential for every practician to have basic knowledge of these methods. We can always systematically define every optimization problem by the triplet of arguments (x, f (x),X)where x is an n-dimensional vector called decision variable and f (x) an objective function. Moreover, X denotes a sub- set of R called an admissible region or a feasible region that is prescribed generally by a set of equality and/or inequality equations called constraints. Using these arguments, the optimization problem can be described generally and simply as follows: [Problem]min f (x) subject to x ∈ X. The maximization problem can be handled in the same way as the mini- mization problem just by http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Frontiers in Computing Technologies for Manufacturing ApplicationsMetaheuristic Optimization in Certain and Uncertain Environments

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Publisher
Springer London
Copyright
© Springer-Verlag London Limited 2007
ISBN
978-1-84628-954-5
Pages
13 –75
DOI
10.1007/978-1-84628-955-2_2
Publisher site
See Chapter on Publisher Site

Abstract

Metaheuristic Optimization in Certain and Uncertain Environments 2.1 Introduction Until now, a variety of optimization methods have been used as effective tools for making a rational decision in manufacturing systems and will surely continue to do so. By virtue of the outstanding progress in computers, many applications have been carried out in the real world using commercial software that has been developed greatly. To understand the proper usage of software and the adequate choice of optimization method through revealing merits and demerits compared with recent metaheuristic approaches, it is essential for every practician to have basic knowledge of these methods. We can always systematically define every optimization problem by the triplet of arguments (x, f (x),X)where x is an n-dimensional vector called decision variable and f (x) an objective function. Moreover, X denotes a sub- set of R called an admissible region or a feasible region that is prescribed generally by a set of equality and/or inequality equations called constraints. Using these arguments, the optimization problem can be described generally and simply as follows: [Problem]min f (x) subject to x ∈ X. The maximization problem can be handled in the same way as the mini- mization problem just by

Published: Jan 1, 2007

Keywords: Local Search; Tabu Search; Distribution Center; Tabu List; Uncertain Environment

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