- Category:
- matlab
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[Matlab]
[源码]
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- Update:
- 2014-02-08
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- 朱坤鸿
Description: Parsopoulos etc. penalty function method, the use of non-fixed multi-stage mapping function constrained optimization problem for transformation, reuse PSO algorithm for solving the problem after the conversion, the simulation results show that the relative genetic algorithm PSO algorithm has more advantages, but its design is too complicated penalty function is not conducive to solving Hu retention policies such as the use of feasible solutions processing constraints, on the one hand to retain only feasible solution when updating the store all particles, on the other hand all the particles are in the initialization phase values from the feasible solution space, however, the initial feasible solution space For many the problem is difficult to determine Ray and put forward the principle of a multi-layer particle swarm information sharing strategies to deal with constraints, according to the constraint matrix using multi Pareto superior sorting mechanism to generate partic
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PSOBP502.m