期刊
COMPUTERS & OPERATIONS RESEARCH
卷 38, 期 12, 页码 1792-1804出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2011.02.014
关键词
Nonconvex mixed-integer nonlinear programming; Local search; Auxiliary function
类别
资金
- National Natural Science Foundation of China [61070020, 10931003, 60773126]
- National Key Basic Research Special Foundation (NKBRSF) of China [2011CB808000]
- Research Fund for the Doctoral Program (RFDP) of China [20093514110004]
We consider in this paper the nonconvex mixed-integer nonlinear programming problem. We present a mixed local search method to find a local minimizer of an unconstrained nonconvex mixed-integer nonlinear programming problem. Then an auxiliary function which has the same global minimizers and the same global minimal value as the original problem is constructed. Minimization of the auxiliary function using our local search method can escape successfully from previously converged local minimizers by taking increasing values of parameters. For the constrained nonconvex mixed-integer nonlinear programming problem, we develop a penalty based method to convert the problem into an unconstrained one, and then use the above method to solve the later problem. Numerical experiments and comparisons on a set of MINLP benchmark problems show the effectiveness of the proposed algorithm. (C) 2011 Elsevier Ltd. All rights reserved.
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