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摘要
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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.
Keyword:
Evolutionary Algorithms
Constrained optimization
Penalty function design
Genetic coding
Adaptive Evolutionary Algorithms
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期刊
IF:
4.3
论文数:
1.6K
被引数:
3.6K
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引用论文
A hybrid genetic algorithm and particle swarm optimization for multimodal functions一种求解多峰函数的混合遗传粒子群算法

