Solution for integer linear bilevel programming problems using orthogonal genetic algorithm

An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit programming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on...

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Bibliographic Details
Published in:Journal of systems engineering and electronics 2014-06, Vol.25 (3), p.443-451
Main Authors: Li, Hong, Zhang, Li, Jiao, Yongchang
Format: Article
Language:English
Subjects:
Algorithms
Crossovers
Design engineering
Factor analysis
Genetic algorithms
Integers
Operators
Programming
二层规划问题
交叉算子
因子分析
整数
正交设计
线性规划问题
设计方法
遗传算法
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Summary:An integer linear bilevel programming problem is firstly transformed into a binary linear bilevel programming problem, and then converted into a single-level binary implicit programming. An orthogonal genetic algorithm is developed for solving the binary linear implicit programming problem based on the orthogonal design. The orthogonal design with the factor analysis, an experimental design method is applied to the genetic algorithm to make the algorithm more robust, statistical y sound and quickly convergent. A crossover operator formed by the orthogonal array and the factor analysis is presented. First, this crossover operator can generate a smal but representative sample of points as offspring. After al of the better genes of these offspring are selected, a best combination among these offspring is then generated. The simulation results show the effectiveness of the proposed algorithm.
ISSN:1004-4132
1004-4132
DOI:10.1109/JSEE.2014.00051