一种改进的禁忌搜索算法及其在连续全局优化中的应用  

An Improved Tabu Search Algorithm for Continuous Global Optimization Problems

作　　者：郭崇慧[1] 岳晓晖[2] 

机构地区：[1]大连理工大学系统工程研究所,辽宁大连116024 [2]大连理工大学应用数学系,辽宁大连116024

出　　处：《运筹与管理》2007年第4期6-11,共6页Operations Research and Management Science

基　　金：国家自然科学基金资助项目(10571018)

摘　　要：禁忌搜索算法是一种元启发式的全局优化算法,是局部搜索算法的一种推广,已被成功地应用于许多组合优化问题中。本文针对有界闭区域上的连续函数全局优化问题,提出了一种改进的禁忌搜索算法,并进行了理论分析和数值实验。数值实验表明,对于连续函数全局优化问题的求解该算法是可行有效的,并且结构简单,迭代次数较少,是一种较好的全局启发式优化算法。Tabu search algorithm is a meta-heuristic global optimization algorithm, which has been successfully applied to a variety of combination optimization problems. This paper proposes an improved memory-based tabu search algorithm, which is applied as an approach to solve continuous function optimization on closed bounded region. The proposed algorithm is very simple and easy to implement. Numerical results illustrate that this algorithm is feasible, effective, and very suitable for continuous global optimization.

关 键 词：运筹学 元启发式算法 禁忌搜索算法 连续全局优化 

分 类 号：O229[理学—运筹学与控制论] TP301[理学—数学]