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非线性规划问题全局优化的模拟退火法
引用本文:胡山鹰,陈丙珍,何小荣,沈静珠.非线性规划问题全局优化的模拟退火法[J].清华大学学报(自然科学版),1997(6).
作者姓名:胡山鹰  陈丙珍  何小荣  沈静珠
作者单位:清华大学化学工程系
基金项目:国家教委留学回国人员科研资助
摘    要:在无约束非线性规划问题全局优化的模拟退火算法基础上,进行有约束问题求解的进一步探讨,对不等式约束条件提出了检验法和罚函数法的处理方法,对等式约束条件开发了罚函数法和解方程法的求解步骤,并进行了分析比较,从而形成了完整的求取非线性规划问题全局优化的模拟退火算法。通过对文献例题的计算,表明所提出的方法能够快速有效地求出有约束非线性规划问题的全局最优解

关 键 词:全局优化  模拟退火  等式约束  不等式约束  罚函数

Simulated annealing method on global optimization of nonconvex NLP problems
Hu Shanying,Chen Bingzhen,He Xiaorong,Shen Jingzhu.Simulated annealing method on global optimization of nonconvex NLP problems[J].Journal of Tsinghua University(Science and Technology),1997(6).
Authors:Hu Shanying  Chen Bingzhen  He Xiaorong  Shen Jingzhu
Institution:Hu Shanying,Chen Bingzhen,He Xiaorong,Shen Jingzhu Department of Chemical Engineering,Tsinghua University,Beijing 100084
Abstract:On the basis of simulated annealing(SA) algorithm for nonconstraint nonlinear programming(NLP) problems, an improvement and further approach to global optimization of SA on nonconvex NLP with constraints is introduced. To inequality constraints, a check procedure and a penalty function procedure are proposed, and equality constraints are dealt with by a procedure of solving equations in which tear equations may be converged by an iterating way or a penalty function way. As a result, an SA algorithm for global optimization on nonconvex NLP problems with constraints is developed. Results of examples show that the proposed approach is better than existing methods.
Keywords:global optimization  simulated annealing  equality constraint  inequality constraint  penalty function  
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