应用改进蚁群算法求解柔性作业车间调度问题  

Solving Flexible Job-shop Scheduling Problem Based on an Improved Ant Colony Optimization Algorithm

作　　者：刘志勇[1] 吕文阁[1] 谢庆华[1] 何明玉[1] 杨杰[1] 刘雄辉[1] 

机构地区：[1]广东工业大学机电工程学院,广东广州510006

出　　处：《工业工程与管理》2010年第3期115-119,共5页Industrial Engineering and Management

摘　　要：将蚁群算法信息素更新规则进行改进,规定只有产生至今最优解的蚂蚁才能释放信息素,且只更新全局信息素,减少了传统蚁群算法的时间复杂度,提高了问题的求解效率。分析了柔性作业车间调度的特点,选取三个性能指标作为求解目标,设定其求解优先级,并建立相应的调度模型。将改进蚁群算法应用于柔性作业车间调度算例的求解,与其它算法比较,平均解有很大提高,表明了该算法求解柔性作业车间调度问题的有效性。An improved Ant Colony Optimization（ACO） algorithm was developed,a new pheromone update rule was designed which regulates that only the ant with the best-so-far solution could deposit pheromone and only updated the global pheromone.So the computational time complexity lessened markedly and search efficiency enhanced obviously.Based on the characteristic of Flexible Job-shop Scheduling Problems（FJSP）,the priority of three object functions was set up and then the corresponding optimization model was presented.Several typical FJSPs were chosen as examples to verify the improved algorithm.Compared with other approaches,the improved algorithm performed better than that presented in relative papers averagely;it meant that the improved algorithm was reasonable and feasible for FJSP.

关 键 词：改进蚁群算法 柔性作业车间调度 信息素更新规则 

分 类 号：O224[理学—运筹学与控制论] TP301.6[理学—数学]