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A Single Component Mutation Evolutionary Programming
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DOI：10.1016/j.amc.2009.10.049.png)
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Abstract
En 中文
In this paper, a novel evolutionary programming is proposed for solving the upper and lower bound optimization problems as well as the linear constrained optimization problems. There are two characteristics of the algorithm: first, only one component of the current solution is mutated in each iteration; second, it can solve the linear constrained optimization problems directly without converting it into unconstrained problems. By solving two kinds of the optimization problems, the algorithm can not only effectively find optimal or close to optimal solutions but also reduce the number of function evolutions compared with the other heuristic algorithms. (C) 2009 Elsevier Inc. All rights reserved.
Keywords:
Global optimization
Constrained optimization problems
Heuristic
Evolutionary programming
Genetic algorithms
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