一类模拟退火算法与遗传算法混合优化策略  

Global Optimization Algorithm and Simulated Annealing Alogorithm mixed strategy

作　　者：李建勋 文海玉[2] 

机构地区：[1]黑龙江省招考办,黑龙江哈尔滨150001 [2]哈尔滨工业大学,黑龙江哈尔滨150001

出　　处：《黑龙江工程学院学报》2010年第2期69-71,共3页Journal of Heilongjiang Institute of Technology

摘　　要：提出一类模拟退火算法(GA)和遗传算法(SA)的混合策略。算法结构上,提出模拟退火算法与遗传算法相结合,既发挥模拟退火算法搜索面广、遗传算法收敛快的优点,又克服前者收敛速度较慢而后者收敛容易早熟的问题。在算法操作细节上,加入杰出个体保护策略及自适应调整的遗传操作,以及增加记忆功能的模拟退火操作与收敛准则。从而既防止算法陷入局部最优,又提高收敛速度及搜索效率。In this paper,we proposed Global Optimization Algorithm（GA） and Simulated Annealing Algorithm（SA） mixed strategy.With regard to the algorithm structure,it comes up with the idea of combining the Simulated Annealing Algorithm with the Genetic Algorithm,putting to the best use the Simulated Annealing Algorithm which explores the full model space and the Genetic Algorithm which converges rapidly,as well as overcoming the problems of the former which works at low convergence speed and the premature of the latter.The strategy of protecting elitists and the genetic operation of adaptive adjustment,and the operation of convergence norms and simulated annealing with memorizing function are applied into the details of algorithm,so as to prevent the algorithm from local optimum and to raise the convergence speed as well as the search efficiency.

关 键 词：模拟退火算法 遗传算法 优化 

分 类 号：O242.1[理学—计算数学]