| This research is aimed to optimize the scheduling strategy for assembly job shop system,such as the braider assembly job shop.Optimization for static scheduling and rescheduling under dynamic condition in assembly job shop scheduling problem（AJSSP）are executed in this research.Based on the production data collected from realistic braider assembly job shop,cased studies are designed to analyze efficiency of methods.A four-month field survey on the assembly workshop of braiding machine equipment was carried out.Through this investigation,the author learned that the main problem in this manufacturing system is tardiness of delivery time.Based on the demand of decreasing tardiness,the principle objective of this research is designed to minimize the Cmax（maximum of tasks’ completion time）.Resource data,products’ structure and processing time are collected during the survey.（1）The static scheduling strategy is optimized in this research.Build mathematic model for AJSSP,then the DPSO（Discrete Particle Swarm Optimization）algorithm and IPSO（Improved Particle Swarm Optimization）algorithm are applied to solve the model respectively.Results of case study indicated that two methods are applicable in this problem and IPSO method is preferable in this process.Form the analysis of parameter,the best parameter combination for this case is obtained.（2）This research also considers the effect of dynamic factor（absent of operator or machine breakdown）in the production process.In order to minimize the maximum completion time and insure stability,a linear weighted method is employed to combine the two objectives and the IPSO algorithm is used to solve the rescheduling problem in assembly job shop.A dynamic rescheduling case is considered to verify the feasibility of method and analyze the weighted parameters. |
