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H. C. Li and Y. P. Wang, “A hybrid genetic algorithm for solving a class of nonlinear bilevel programming problems,” Proceedings of Simulated Evolution and Learning- 6th International Conference, SEAL, pp. 408–415, 2006.

has been cited by the following article:

• TITLE: An Evolutionary Algorithm Based on a New Decomposition Scheme for Nonlinear Bilevel Programming Problems

  AUTHORS: Hecheng LI, Yuping WANG

  KEYWORDS: Nonlinear Bilevel Programming, Decomposition Scheme, Evolutionary Algorithm, Optimal Solutions

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.3 No.1, January 20, 2010

  ABSTRACT: In this paper, we focus on a class of nonlinear bilevel programming problems where the follower’s objective is a function of the linear expression of all variables, and the follower’s constraint functions are convex with respect to the follower’s variables. First, based on the features of the follower’s problem, we give a new decomposition scheme by which the follower’s optimal solution can be obtained easily. Then, to solve efficiently this class of problems by using evolutionary algorithm, novel evolutionary operators are designed by considering the best individuals and the diversity of individuals in the populations. Finally, based on these techniques, a new evolutionary algorithm is proposed. The numerical results on 20 test problems illustrate that the proposed algorithm is efficient and stable.