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! P' f4 @8 l/ K% {& D- u& h5 |' W规模为N的种群中的每个个体都要针对M个目标函数和种群中的N-1个个体进行比较,复杂度为O(MN),因此种群中的N个个体都比较结束的复杂度为O(MN2),即每进行一次Pareto分级的时间复杂度为O(MN2)。
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6 n) F+ V! f5 z% ~# z% E2 s该算法需要保存两个量:, H! \/ z' [. r. F; d
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(1).支配个数np。该量是在可行解空间中可以支配个体p的所有个体的数量。7 _% R4 y- d3 N
1 f0 D3 J5 ~, [3 t(2).被支配个体集合SP。该量是可行解空间中所有被个体p支配的个体组成的集合。3 ?4 w; x, f6 f0 @ Z k; J( H
1 R! B$ z# Y# C) Q3 [' dmatlab代码:/ l: Q0 P2 A1 K m
N1 G0 Q4 |, x$ }. E(注意PopObj填入的多目标的函数值,如果有两个目标,100个个体,那么就是100*2的矩阵,nSort是前沿面的编号)3 _* q! {0 O. {7 S6 ]3 U
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- function [FrontNO,MaxFNO] = NDSort(PopObj,nSort)
- %NDSort - Do non-dominated sorting on the population by ENS
- %
- % FrontNO = NDSort(A,s) does non-dominated sorting on A, where A is a
- % matrix which stores the objective values of all the individuals in the
- % population, and s is the number of individuals being sorted at least.
- % FrontNO(i) means the number of front of the i-th individual.
- %
- % [FrontNO,K] = NDSort(...) also returns the maximum number of fronts,
- % except for the value of inf.
- %
- % In particular, s = 1 stands for find only the first non-dominated
- % front, s = size(A,1)/2 stands for sort only half of the population
- % (which is often used in the algorithm), and s = inf stands for sort the
- % whole population.
- %
- % Example:
- % [FrontNO,MaxFNO] = NDSort(PopObj,1)
- [N,M] = size(PopObj);
- FrontNO = inf(1,N);
- MaxFNO = 0;
- [PopObj,rank] = sortrows(PopObj);
- while sum(FrontNO<inf) < min(nSort,N)
- MaxFNO = MaxFNO + 1;
- for i = 1 : N
- if FrontNO(i) == inf
- Dominated = false;
- for j = i-1 : -1 : 1
- if FrontNO(j) == MaxFNO
- m = 2;
- while m <= M && PopObj(i,m) >= PopObj(j,m)
- m = m + 1;
- end
- Dominated = m > M;
- if Dominated || M == 2
- break;
- end
- end
- end
- if ~Dominated
- FrontNO(i) = MaxFNO;
- end
- end
- end
- end
- FrontNO(rank) = FrontNO;
- end' D& I* w$ ?8 V( }6 `
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