期刊
COGNITIVE COMPUTATION
卷 2, 期 2, 页码 97-119出版社
SPRINGER
DOI: 10.1007/s12559-010-9039-2
关键词
Evolutionary Algorithms; Constrained optimization; Penalty function design; Genetic coding; Adaptive Evolutionary Algorithms
Nature has always been a source of great inspiration for engineers and mathematicians. Evolutionary Algorithms are the latest in a line of natural-based innovations which have had a profound effect on the application of optimization in science and engineering. Although based on nature, Evolutionary Algorithms are nonetheless distinctly different from natural evolution in several areas. This paper outlines early and recent developments of Evolutionary Algorithms while covering those areas of difference. Practical issues related to the use of Evolutionary Algorithms, key parameters that affect the quality of the search and impact of user choices in problem formulation are also covered in this paper.
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