Research On A Company’s Flexible Job Shop Scheduling Problem Based On Dynamic Events

In the production process of the flexible job shop,due to the occurrence of dynamic events such as emergency order insertion and machine failure,the operation of the existing scheduling scheme is inefficient or even interrupted from time to time.How to actively respond to frequent dynamic events and reasonably carry out process planning and workshop scheduling can ensure the on-time delivery of orders and improve customer satisfaction,which is a hot issue in the current research on flexible job shop integration optimization.At the same time,the research on the integration of process planning and scheduling based on dynamic events has certain practical guiding significance for improving the production efficiency of enterprises and enhancing their own competitiveness.This paper takes M company’s flexible workshop as the research object,analyzes the problems of high delivery delay rate and low customer satisfaction,and proposes an integrated optimization scheme of process planning and scheduling based on dynamic events.Firstly,determined the order priority,the fuzzy trigonometric function is applied to the expression of processing time,and considered two dynamic events,emergency order insertion and machine failure.An integrated model of process planning and scheduling with fuzzy completion time and scheduling deviation as optimization goals is constructed,and verify the validity of the proposed model.It lays a foundation for the study of flexible job shop rescheduling problem.Secondly,an improved bat algorithm is designed.Based on the traditional bat algorithm,the algorithm introduces an external elite bat set,global learning strategy,mutation operation and dynamic adjustment mechanism.It achieves multi-objective optimization,enhances the global search ability of the algorithm and the learning ability of the population,avoids the algorithm from falling into prematurity.And a G1-IEVM-ITOPSIS method is proposed to select the optimal solution for the Pareto solution set based on the importance of each optimization objective.The improved bat algorithm,traditional bat algorithm and improved genetic algorithm are tested with examples to verify the effectiveness of the algorithm in this paper.Finally,combined with the processing information of M company’s flexible job shop,after solving it,the scheduling scheme of completion time,scheduling deviation and delivery delay rate are optimized under two dynamic events is obtained.The integrated optimization solution of process planning and scheduling based on dynamic events proposed in this paper can effectively reduce the impact of emergency order insertion and machine failure on production,and provide M company with a fast-response and efficient workshop scheduling scheme.The delay rate of its delivery date was reduced by 33%,which in turn improved the company’s service evaluation,obtained higher customer satisfaction,and provided a reference for enterprises to achieve scientific production and management.