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Evolutionary algorithms for constrained engineering problems
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AI
DOI：10.1016/0360-8352(96)00037-X.png)
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Abstract
En 中文
Evolutionary computation techniques have been receiving increasing attention regarding their potential as optimization techniques for complex problems. Recently these techniques were applied in the area of industrial engineering; the most-known applications include scheduling and sequencing in manufacturing systems, computer-aided design, facility layout and location problems, distribution and transportation problems, and many others. Industrial engineering problems usually are quite hard to solve due to a high complexity of the objective functions and a significant number of problem-specific constraints; often an algorithm to solve such problems requires incorporation of some heuristic methods. In this paper we concentrate on constraint handling heuristics for evolutionary computation techniques. This general discussion is followed by three test case studies: truss structure optimization problem, design of a composite laminated plate, and the unit commitment problem. These are typical highly constrained engineering problems and the methods discussed here are directly transferrable to industrial engineering problems. Copyright (C) 1996 Elsevier Science Ltd
Keywords:
THERMAL UNIT COMMITMENT
GENETIC ALGORITHMS
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6.5
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1.0W
Citations:
3.8W
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