Journal
ENGINEERING OPTIMIZATION
Volume 46, Issue 3, Pages 361-376Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/0305215X.2013.772601
Keywords
co-evolutionary algorithm; bilevel programming problems; approximate solutions; optimal solutions
Funding
- National Natural Science Foundation of China [61065009]
- Natural Science Foundation of Qinghai Province [2011-z-756]
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The bilevel programming problem involves two optimization problems, which is hierarchical, strongly NP-hard and very challenging for most existing optimization approaches. An efficient universal co-evolutionary algorithm is developed in this article to deal with various bilevel programming problems. In the proposed algorithm, evolutionary algorithms are used to explore the leader's and the follower's decision-making spaces interactively. Unlike other existing approaches, in the suggested procedure the follower's problem is solved in two phases. First, an evolutionary algorithm is run for a few generations to obtain an approximation of lower level solutions. In the second phase, from all approximate solutions obtained above, only a small number of good points are selected and evolved again by a newly designed multi-criteria evolutionary algorithm. The technique refines some candidate solutions and can efficiently reduce the computational cost of obtaining feasible solutions. Proof-of-principle experiments demonstrate the efficiency of the proposed approach.
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