计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2009年
31期
30-33
,共4页
粒子群算法%自组织%种群多样性%旅行商问题(TSP)
粒子群算法%自組織%種群多樣性%旅行商問題(TSP)
입자군산법%자조직%충군다양성%여행상문제(TSP)
Particle Swarm Optimization (PSO)%self-organizing%population diversity%Traveling Salesman Problem(TSP)
针对粒子群算法(PSO)的早熟收敛现象,从种群多样性出发,基于自组织临界性特点改进PSO算法的参数设置,采用自组织的惯性权重和加速系数,并增加了变异算子.借鉴交换子和交换序概念,设计出了能直接在离散域进行搜索的改进的自组织PSO算法.用于旅行商问题(TSP)的求解,并与基本及其他典型改进PSO算法进行性能比较.实验结果证实改进的自组织PSO算法是有效的.
針對粒子群算法(PSO)的早熟收斂現象,從種群多樣性齣髮,基于自組織臨界性特點改進PSO算法的參數設置,採用自組織的慣性權重和加速繫數,併增加瞭變異算子.藉鑒交換子和交換序概唸,設計齣瞭能直接在離散域進行搜索的改進的自組織PSO算法.用于旅行商問題(TSP)的求解,併與基本及其他典型改進PSO算法進行性能比較.實驗結果證實改進的自組織PSO算法是有效的.
침대입자군산법(PSO)적조숙수렴현상,종충군다양성출발,기우자조직림계성특점개진PSO산법적삼수설치,채용자조직적관성권중화가속계수,병증가료변이산자.차감교환자화교환서개념,설계출료능직접재리산역진행수색적개진적자조직PSO산법.용우여행상문제(TSP)적구해,병여기본급기타전형개진PSO산법진행성능비교.실험결과증실개진적자조직PSO산법시유효적.
To alleviate the premature convergence of basic particle swarm optimization (PSO), an improved self-organized particle swarm optimization(SOPSO) algorithm is proposed, whose parameter setting are improved based on the characteristics of self-organizing criticality in the interest of the diversity of population.That is, the self-organizing inertia weight and acceleration coefficients are applied and the mutation operator is introduced.In view of the concept of "Swap operator" and "Swap sequence",the improved SOPSO algorithm which can search in the discrete domain directly is designed to solve the traveling salesman problem (TSP).Then compare the results of the improved algorithm with those of the basic PSO and other improved PSO algorithm.The results show that the improved SOPSO algorithm is effective.
