文件名称:nsga2.tar
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这段代码描述多目标遗传算法NSGAII算法的实现,抓要包含三部分:Non-dominated sort, Crowding distance assignment, the selection process来找到pareto-front-The basic operations being performed and the worst case complexities associated with are as follows:
Multi-objective evolutionary algorithms which uses non-dominated sorting to find pareto front. It is consist of tree parts:
• Non-dominated sort returns a list of the non-dominated fronts F. (O(mN 2 ))
• Crowding distance assignment is O(mNlogN)
• The crowed comparison operator (Sort on ≥ n) guides the selection process at the various stages of the algorithm towards a uniformly spread out Pareto-optimal front. (O(2Nlog(2N)))
Multi-objective evolutionary algorithms which uses non-dominated sorting to find pareto front. It is consist of tree parts:
• Non-dominated sort returns a list of the non-dominated fronts F. (O(mN 2 ))
• Crowding distance assignment is O(mNlogN)
• The crowed comparison operator (Sort on ≥ n) guides the selection process at the various stages of the algorithm towards a uniformly spread out Pareto-optimal front. (O(2Nlog(2N)))
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下载文件列表
nsga2/
nsga2/nsga2.pyc
nsga2/nsga2.py
nsga2/test_nsga2.py
nsga2/__init__.py
nsga2/nsga2.pyc
nsga2/nsga2.py
nsga2/test_nsga2.py
nsga2/__init__.py
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