A Computational Method Based on Adaptive Genetic Algorithm for Bilevel Linear Programming

被引：0
|
作者：
Wang, Guangmin
Wan, Zhongping
Wang, Xianjia
机构：
来源：
ADVANCES IN BUSINESS INTELLIGENCE AND FINANCIAL ENGINEERING | 2008年 / 5卷
关键词：
bilevel linear programming; genetic algorithm; fitness value; adaptive operator probabilities; crossover and mutation;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Bilevel programming is a useful tool for modeling decentralized decisions with hierarchical structure. So, many methods are proposed to solve this problem. And the genetic algorithm is an alternative to conventional approaches to find solution to the bilevel programming. In this paper, the performance of this proposed algorithm is illustrated by the randomly generating examples after describing the steps of the. adaptive genetic algorithm for solving the bilevel linear programming problem to overcome the difficulty of determining the probabilities of crossover and mutation.
引用
收藏
页码：1041 / 1048
页数：8
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