Integral global minimization: Algorithms, implementations and numerical tests

被引:34
|
作者
Zheng, Q [1 ]
Zhuang, DM [1 ]
机构
[1] MT ST VINCENT UNIV,DEPT MATH & COMP STUDIES,HALIFAX,NS B3M 2J6,CANADA
关键词
integral global minimization; Monte Carlo implementation; test problems; discontinuous penalty method; robustification;
D O I
10.1007/BF01099651
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
The theoretical foundation of integral global optimization has become widely known and well accepted [4],[24],[25]. However, more effort is needed to demonstrate the effectiveness of the integral global optimization algorithms. In this work we detail the implementation of the integral global minimization algorithms. We describe how the integral global optimization method handles nonconvex unconstrained or box constrained, constrained or discrete minimization problems. We illustrate the flexibility and the efficiency of integral global optimization method by presenting the performance of algorithms on a collection of well known test problems in global optimization literature. We provide the software which solves these test problems and other minimization problems. The performance of the computations demonstrates that the integral global algorithms are not only extremely flexible and reliable but also very efficient.
引用
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页码:421 / 454
页数:34
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