基于交替迭代遗传算法的多级车间生产计划与调度的集成优化

为了提高多级生产系统的运作效率,研究了一类多周期的多级车间生产计划与调度的集成优化问题,该生产系统由一级混批Job-shop车间和一级混流装配车间串联而成.首先建立了该类集成优化问题的混合整数规划模型,该模型从上下游生产车间的需求关系出发,综合考虑上下游车间的物料平衡、设备负荷以及开工位置等约束条件,同时满足优化上下游生产线的费用目标.然后提出了一种交替式混合遗传协调优化算法求解该集成优化问题,其主要思想是给定计划用一种混合遗传算法求调度,反过来给定已求调度用另一种混合遗传算法求取新计划,如此不断交替使用2种混合遗传算法实现计划与调度的同时优化.仿真结果证明了该方法的可行性和有效性.

Integrated production planning and scheduling of multi-stage workshop based on alternant iterative genetic algorithm

In order to improve the operational efficiency of multi-stage production system,an integrated multi-period multi-workshop production planning and scheduling problem is explored.The production system consists of a mixed-batch Job-shop workshop in series with a mixed-model assembly workshop.An integrated optimization model of the production planning and scheduling is formulated based on nonlinear mixed integer programming.In this model the constraints such as material balance,device capacity,and start position,etc.,are taken into account and the demand relations between the upstream workshop and the downstream workshop are considered synchronously.The cost objectives of the two workshops can be optimized simultaneously.Then an alternant iterative method by hybrid genetic algorithm is employed to solve it,which operates by the following steps: a plan is given to find a schedule by a hybrid genetic algorithm;in turn,a schedule is given to find a new plan using another hybrid genetic algorithm.Two hybrid genetic algorithms are alternately run to optimize the plan and schedule simultaneously.Simulation results show that the proposed method is feasible and effective.