| Algorithm for solving the bi-level decision making problem with continuous variables in the upper level based on genetic algorithm |
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| 作者姓名： | 肖剑 |
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| 作者单位： | College of |
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| 摘 要： | 1 Introduction a The bi-level decision-making is a complex majorized problem. Its effective solution is not easy to obtain by traditional majorized methods. Reported methods to solve the bi-level decision making problem with continuous variables include neural network 1], Monte Carlo simulated annealing algorithm 2], etc. However, the efficiency and accuracy of such neural network methods are ideal and accompanied with a long iterative time and a slow convergence speed. In this paper, the …
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| 关 键 词： | 连续变量 遗传算法 优化方案 蒙特卡洛模拟法 |
Algorithm for solving the bi-level decision making problem with continuous variables in the upper level based on genetic algorithm |
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| XIAO Jian,CHEN Yi-hua.Algorithm for solving the bi-level decision making problem with continuous variables in the upper level based on genetic algorithm[J].Journal of Chongqing University,2005,4(1):59-62. |
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| Authors: | XIAO Jian CHEN Yi-hua |
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| Abstract: | Based on genetic algorithms, a solution algorithm is presented for the bi-level decision making problem with continuous variables in the upper level in accordance with the bi-level decision making principle. The algorithm is compared with Monte Carlo simulated annealing algorithm, and its feasibility and effectiveness are verified with two calculating examples. |
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| Keywords: | bi-level decision making Monte Carlo simulated annealing genetic algorithms |
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