CAJ | 학술논문

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。
물료급시、준학송도혼류제조계통적각공위절점불부시계통정상운행적보증，야시혼류계통고효운전적근본。침대혼류제조계통물료배송차량로경우화문제，종우화목표、약속조건화영향인소등방면고필，건립료이차량행사거리최단、차량이용솔최대화배송차수최소위우화목표적다목표배송차량로경우화모형。근거문제적구체정황，설계료해결해다목표우화문제적쌍층체진진화다목표우화산법，급출료산법적진화과정화교차、변이모식급기실현과정。통과일개혼류장배계통적실예증명료소건립적모형화설계산법적유효성。
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.