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Evolutionary algorithms approach to the solution of mixed integer non-linear programming problems
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DOI：10.1016/S0098-1354(00)00653-0.png)
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The global optimization of mixed integer non-linear problems (MINLP), constitutes a major area of research in many engineering applications. In this work, a comparison is made between an algorithm based on Simulated Annealing (M-SIMPSA) and two Evolutionary Algorithms: Genetic Algorithms (GAs) and Evolution Strategies (ESs). Results concerning the handling of constraints, through penalty functions, with and without penalty parameter setting, are also reported. Evolutionary Algorithms seem a valid approach to the optimization of non-linear problems. Evolution Strategies emerge as the best algorithm in most of the problems studied. (C) 2001 Elsevier Science Ltd. All rights reserved.
Keyword:
evolutionary algorithms
genetic algorithms
evolution strategies
mixed integer non-linear programming
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