基于遗传算法的混合优化策略研究  

Study of Hybrid Optimization Strategy Based on Genetic Algorithm

作　　者：路景[1] 周春艳[1] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083

出　　处：《计算机技术与发展》2007年第3期144-146,149,共4页Computer Technology and Development

摘　　要：最优化问题是工程设计、科学研究、经济管理等众多领域经常遇到的一类问题。随着待解决问题范围的不断扩大以及优化算法研究的不断深入,混合优化策略已成为解决大规模、高复杂度优化问题的一种重要而有效的方法。介绍了遗传算法、贪婪法、模拟退火算法、禁忌搜索的基本原理,阐述了各种算法的优缺点;针对各单一算法存在的缺陷和不足,对三种以遗传算法为主体框架的混合优化算法进行了分析;最后,指出了混合优化算法存在的问题及今后的发展方向。Optimization problems often emerge in many rids, such as engineering design, science research and economic management. With the range of problems that need m be solved enlarges and the research of optimization algorithms is more and more deep, hybrid optimization strategy has become an important and effective way to solve large - scale and complicated optimization problems. This paper introduces the basic ideas of genetic algorithm, greedy algorithm, stimulated annealing and tabu search briefly and expounds the merits and defects of these algorithms. According to the disadvantages of thee algorithms, three hybrid optimization algorithms based on genetic algorithm are analyzed. Finally,the existing problems and future development in hybrid optimization algorithms are discussed.

关 键 词：遗传算法 贪婪法 模拟退火 禁忌搜索 混合优化策略 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]