摘要
基于模拟退火算法提出了一种结构优化设计的校正多级多点模拟退火算法(CMLPSA)。该算法从随机生成的一组试算点选择每个候选设计,实现一种高效的搜索策略。因而,CMLPSA是处理一组设计而不是一个单一的试算点。对可行和不可行的中间设计采用多点策略,即对可行情况,优化变量的变动是随着成本函数的当前变化率而变化;不可行情况下,在当前退火周期中生成的每个可行的试算点附近,进行第四阶近似直线搜索。此外,CMLPSA包括多级退火策略,通过同时(整体级)或逐个(局部级)变动所有的设计变量生成试算点。基于优化过程中的趋势,执行全局或局部搜索。数值算例验证了CMLPSA算法的有效性,可应用于结构优化。
An optimization algorithm based on Simulated Annealing is presented. The algorithm is called as corrected multi-level and multi-point simulated annealing（ CMLPSA）. An advanced search mechanism where each candidate design is selected from a group of trial points generated randomly is implemented. Therefore,CMLPSA is in principle similar to meta-heuristic algorithms dealing with a population of designs rather than with a single trial point such as it is usually done in classical simulated annealing. The multi-point strategy is adopted for both feasible and infeasible intermediate designs. In the feasible case,the perturbations given to optimization variables are forced to follow the current rate of change exhibited by the cost function. In the infeasible case,4th order approximate line search is performed in the neighbourhood of each feasible trial point generated in the current annealing cycle. Furthermore,CMLPSA includes a multi-level annealing strategy where trial points are generated by perturbing all design variables simultaneously（ global level） or one by one（ local level）. Global or local search is performed based on the current trend in the optimization process. The numerical example is given to illustrate the efficiency and exactness of the proposed method in structural optimization.
出处
《建筑科学》
CSCD
北大核心
2017年第3期25-32,共8页
Building Science
基金
国家自然科学基金项目(51378124)
关键词
模拟退火算法
多级搜索
优化设计
优化算法
桁架结构
simulated annealing algorithm
multi-level search
optimization design
optimization algorithm
truss structure
