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Bilevel linear programming,which consists of the objective functions of the upper level and lower level,is a useful tool for modeling decentralized decision problems. Various methods are proposed for solving this problem.Of all the algorithms,the ge- netic algorithm is an alternative to conventional approaches to find the solution of the bilevel linear programming.In this paper,we describe an adaptive genetic algorithm for solving the bilevel linear programming problem to overcome the difficulty of determining the probabilities of crossover and mutation.In addition,some techniques are adopted not only to deal with the difficulty that most of the chromosomes may be infeasible in solving constrained optimization problem with genetic algorithm but also to improve the efficiency of the algorithm.The performance of this proposed algorithm is illustrated by the examples from references. 相似文献
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半无限规划的一种离散逼近法 总被引:1,自引:0,他引:1
首先根据K-收敛理论及有限覆盖定理给出了半无限规划问题的一种新的离散方法;然后结合上图收敛性理论证明了半无限规划问题的一些新的收敛性命题;同时也指出了这种新的离散逼近方法与网格逼近法在收敛性及收敛速度上有一些相似的结论成立,但其在关于SIP问题收敛性和收敛结果的检验上比其他方法更为方便。 相似文献
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