Production Scheduling Optimization Based on Order Priority and Improved Particle Swarm Algorithm
In order to solve the problems of disorderly order scheduling,long order delay time,and high production cost in the production process,focusing on the scheduling of flexible assembly lines,an order priority rule based on order urgency was designed,and a mathematical model for production scheduling was established based on this rule.The main optimization objectives were to minimize the maximum completion time,the total delay time of orders within a cycle,and the inventory and energy costs.The improved particle swarm optimization algorithm in bio-inspired intelligent algorithm was used for optimization.The coding and decoding rules for the problem were designed,and an adaptive dynamic acceleration coefficient was introduced to help escape from local optima.Taking a mixed-flow assembly line of a company as an example,simulation experiments were conducted using MATLAB software.The results show that the proposed model and algorithm can effectively solve and optimize the objective functions,validating the effectiveness of the model and algorithm.
production schedulingflexible assembly lineorder priorityimproved particle swarm algorithmMATLAB software
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维普
