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CONVEXIFICATION AND CONCAVIFICATION METHODS FOR SOME GLOBAL OPTIMIZATION PROBLEMS

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【Author】 WU Zhiyou(School of Mathematics and Computer Science, Chongqing Normal University, Chongqing 400047; Department of Mathematics, Shanghai University, Shanghai 200436, China) ZHANG Liansheng(Department of Mathematics, Shanghai University, Shanghai 200436, China) BAI Fusheng(Institute of Mathematics, Fudan University, Shanghai 200433, China) YANG Xinmin(Department of Mathematics and Computer Science, Chongqing Normal University, Chongqing 400047, China)

【摘要】 <正> In this paper, firstly, we propose several convexification and concavification transformations to convert a strictly monotone function into a convex or concave function, then we propose several convexification and concavification transformations to convert a non-convex and non-concave objective function into a convex or concave function in the programming problems with convex or concave constraint functions, and propose several convexification and concavification transformations to convert a non-monotone objective function into a convex or concave function in some programming problems with strictly monotone constraint functions. Finally, we prove that the original programming problem can be converted into an equivalent concave minimization problem, or reverse convex programming problem or canonical D.C. programming problem. Then the global optimal solution of the original problem can be obtained by solving the converted concave minimization problem, or reverse convex programming problem or canonical D.C

【Abstract】 In this paper, firstly, we propose several convexification and concavification transformations to convert a strictly monotone function into a convex or concave function, then we propose several convexification and concavification transformations to convert a non-convex and non-concave objective function into a convex or concave function in the programming problems with convex or concave constraint functions, and propose several convexification and concavification transformations to convert a non-monotone objective function into a convex or concave function in some programming problems with strictly monotone constraint functions. Finally, we prove that the original programming problem can be converted into an equivalent concave minimization problem, or reverse convex programming problem or canonical D.C. programming problem. Then the global optimal solution of the original problem can be obtained by solving the converted concave minimization problem, or reverse convex programming problem or canonical D.C. programming problem using the existing algorithms about them.

【基金】 This research is supported by the National Natural Science Foundation of China(Grant 10271073).
  • 【文献出处】 Journal of Systems Science and Complexity ,系统科学与复杂性学报(英文版) , 编辑部邮箱 ,2004年03期
  • 【分类号】O224
  • 【被引频次】5
  • 【下载频次】25
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