摘要
物料及时、准确送到混流制造系统的各工位节点不仅是系统正常运行的保证,也是混流系统高效运转的根本。针对混流制造系统物料配送车辆路径优化问题,从优化目标、约束条件和影响因素等方面考虑,建立了以车辆行驶距离最短、车辆利用率最大和配送次数最少为优化目标的多目标配送车辆路径优化模型。根据问题的具体情况,设计了解决该多目标优化问题的双层递进进化多目标优化算法,给出了算法的进化过程和交叉、变异模式及其实现过程。通过一个混流装配系统的实例证明了所建立的模型和设计算法的有效性。
Timely and accurately delivering the material to the workstations in the flow-manufacturing system is not only the guarantee of the normal running, but also the fundamental of the efficient operation of the system. For the Material Delivery Vehicle Routing optimization Problem（MDVRP）in the flow manufacturing, the optimization goals, the constraints and the influencing factors are considered, and the multi-objective optimization model is built by considering the shortest travel distance of vehicles, maximizing the utilization of vehicles and minimizing the number of distributions. According to the specific circumstances of the problem, a Double Progressive Evolutionary Multi-Objective Optimization Algorithm （DPEMOA）is designed to solve the multi-objective optimization problem. The two-tier progressive evolutionary process is proposed. The improved genetic operator is implemented, and the specific implementation process is manifested. The validity of the model and algorithm are verified by a case of flow manufacturing system.
出处
《计算机工程与应用》
CSCD
2014年第15期228-234,270,共8页
Computer Engineering and Applications
基金
国家自然科学基金(No.51075142)
国家科技支撑计划(No.201202BAF02B01)
教育部人文社科规划基金项目(No.10YJA630205)
关键词
物料配送
车辆路径优化
进化算法
多目标优化
material delivery
vehicle routing planning
evolution algorithm
multi-objective optimization
