一种改进的蚁群算法在工艺规划与车间调度集成优化中的应用  

Applications of An Improved Ant Colony Optimization ACO Algorithm in Integrated Process Planning and Scheduling

作　　者：王进峰[1] 范孝良[1] 宗鹏程[1] 万书亭[1] 

机构地区：[1]华北电力大学能源动力与机械工程学院,河北保定071003

出　　处：《图学学报》2014年第3期396-401,共6页Journal of Graphics

基　　金：国家自然科学基金资助项目(51177046);中央高校基本科研业务费专项资金资助项目(13MS100;14ZD37);河北省自然科学基金资助项目(E2011502024)

摘　　要：改进标准蚁群算法的执行策略,可提高工艺规划和调度集成问题的求解质量和效率。通过节点集、有向弧/无向弧集、AND/OR关系,建立了基于AND/OR图的工艺规划和调度集成优化模型。提出一种求解工艺规划与车间调度集成问题的改进蚁群优化算法,采用了信息素动态更新策略避免收敛过慢和局部收敛,利用多目标优化策略提高求解质量。仿真结果证明了该算法的有效性。The improvement of standard ant colony optimization (ACO) strategy is important to improve the quality and efficiency for integrated process planning and scheduling (IPPS). A graph-based optimization model for IPPS is constructed by means of node set, directed arc set/undirected arc set and relation of AND/OR. An improved ACO for IPPS is proposed, which avoids the slow convergence and the local convergence by dynamic pheromone update strategy, and improves the quality by multi-objective optimization strategy. The simulation result demonstrates the validity of the proposed algorithm for IPPS.

关 键 词：工艺规划 调度 集成 优化 蚁群算法 

分 类 号：TH166[机械工程—机械制造及自动化] TP278[自动化与计算机技术—检测技术与自动化装置]