The Research On The Coordinated Optimization Scheduling Problems Of Production And Logistics Based On The Differential Evolution Algorithm In The Military Manufacturing Enterprises

Military manufacturing enterprises are the development cornerstone for the equipment manufacturing industry,there they take on heavy responsibility of providing equipment for national economy and national defense construction.The optimization scheduling problems of production and logistics is most important of production plans for the military manufacturing enterprises.In order to improve the production efficiency and reduce the production cost,the two-stage optimization decision of production and transportation is the key to enhance the core competency of enterprises for the military manufacturing enterprises.In this paper,two optimization problems of production and logistic are addressed motivated by a fuse manufacturing enterprise.We formulate the coordinated scheduling models of production and delivery for the finished products where the objective is to maximum the machine utilization and minimize the flow times and delivery costs,respectively.Since the problems proposed in this paper are NP-hard,the intelligent algorithms have obvious advantage for the problems.In this paper,we develop approximate algorithms based on the differential evolution algorithm and improvement strategy,which can provide decision-making suggestions for the management of production and logistic in the industry.The paper is divided into three parts:(1)For the optimization scheduling problems of production and transportation,a parameter adaptive strategy is derived to integrate the differential evolution algorithm.This can improve the ability of global search and local search of the differential evolution algorithm.The mutation operator and crossover operator in real number range are improved such that it can be applied to the optimization of production and logistics based on discrete coding.(2)For the production environment of parallel machines,a coordinated scheduling problem with batching delivery of finished products in the parallel machines where the goal is to minimize the flow time and delivery costs.A heuristic algorithm SPT-DP is designed based on optimal solution properties as initial strategy for the differential evolution algorithm.We develop an improved strategy with insert neighborhood search to the differential evolution algorithm.A lower bound is derived to evaluate the performance of the algorithms proposed in this paper.The experiment results show that the differential evolution algorithm based on the heuristic algorithm SPT-DP is effective and stable.(3)For the production environment of flow shop,a coordinated scheduling problem with delivery of finished products in the two-machine flow shop where the goal is to minimize the flow time and delivery costs.A heuristic algorithm based on Johnson rule is developed as initial strategy for the differential evolution algorithm.A differential evolution algorithm with the variable neighborhood search is designed to improve the algorithm efficiency.Three lower bounds are derived to evaluate the performance of the algorithms proposed in this paper.Experimental simulation results show that the differential evolution algorithm proposed in this paper is effective for the scheduling problem with delivery in the flow shop.