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改进蚁群算法在车间作业调度中的应用研究
引用本文:张利平,吴正佳,王魁,王文.改进蚁群算法在车间作业调度中的应用研究[J].三峡大学学报(自然科学版),2009,31(2):75-78.
作者姓名:张利平  吴正佳  王魁  王文
作者单位:三峡大学,机械与材料学院,湖北,宜昌,443002
摘    要:研究了基于机器最短加工时间的一类车间作业调度问题,建立了多约束的数学模型,为解决蚁群算法收敛性差和易陷入局部最优的问题,提出了一种基于插入移动的领域搜索方法,并使用该领域搜索方法嵌入蚁群算法.采用国际著名的benchmark测试集FT06进行了实例验证,计算结果表明,该算法可收敛到最优值55,且最优值、平均值和标准差都优于蚁群算法,标准差远远小于蚁群算法.

关 键 词:车间作业调度  蚁群算法  邻域搜索

Application of Improved Ant Colony Algorithm to JSP
Zhang Liping,Wu Zhengjia,Wang Kui,Wang Wen.Application of Improved Ant Colony Algorithm to JSP[J].Journal of China Three Gorges University(Natural Sciences),2009,31(2):75-78.
Authors:Zhang Liping  Wu Zhengjia  Wang Kui  Wang Wen
Institution:Zhang Liping Wu Zhengjia Wang Kui Wang Wen (College of Mechanical & Material Engineering, China Three Gorges Univ. , Yichang 443002, China)
Abstract:The job shop problem by the SPT rules is researched. And the mathematical model with multi-restricted condition is set up. In order to solve ant colony algorithm convergence and plunging local optimal value, an improved ant colony algorithm which bases on interval number is developed. It uses local search to improve the result in every circle. And it is examined by means of the international famous benchmark sets FT06. The computation results show that this algorithm can get the optimal value 55. Optimal value, average value and standard deviation are better than ant colony algorithm. The standard deviation in improved ant colony algorithm is much smaller than the one in ant colony algorithm.
Keywords:job shop problem  ant colony algorithm  local search
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