A Genetic Algorithm for Solving a Special Class of Nonlinear Bilevel Programming Problems

Authors:
Hecheng Li;Yuping Wang
Affiliations:
School of Computer Science and Technology, Xidian University, Xi'an, 710071, China and School of Science, Xidian University, Xi'an, 710071, China;School of Computer Science and Technology, Xidian University, Xi'an, 710071, China
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Year:
2007

Citing 2
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Abstract

A special nonlinear bilevel programming problem (BLPP), whose follower-level problem is a convex programming with a linear objective function in y, is transformed into an equivalent single-level programming by using Karush-Kuhn-Tucker (K-K-T) conditions. To solve the equivalent problem effectively, a new genetic algorithm is proposed. First, a linear programming (LP) is constructed to decrease the dimensions of the transformed problem. Then based on a constraint-handling scheme, a second-phase evolving process is designed for some offspring of crossover and mutation, in which the linear property of follower's function is used to generate high quality potential offspring.