摘要
粒子群算法是一种新颖的演化计算技术,具有思想简单、容易实现的优点,被广泛应用于连续空间的优化。结合遗传算法的思想提出一种新的进化方式并用于Job Shop离散空间优化,进一步结合粒子群算法的群体多样性和禁忌搜索算法的集中搜索性提出一种粒子群算法和禁忌搜索算法的混合策略。用Job Shop问题作为测试基准,仿真试验显示混合粒子群算法是可行和有效的。
Particle swarm optimization（PSO） is a novel evolutionary technology, It has the virtue of simple idea and easy to realize and is applied abroadly in sequenced space optimization. A new evolutionary method is given combined with genetic algorithm and is applied in Job Shop dispersed space optimization. Moreover, the swarm variety of PSO and centralized search of taboo search are integrated,and a hybrid policy of PSO and taboo search is proposed. As a test case, Job Shop illustrates that the new hybrid PSO is feasible and effective.
出处
《计算机技术与发展》
2006年第9期109-111,共3页
Computer Technology and Development
基金
安徽省高等学校青年教师科研资助项目(2005jq1062)
