Job shop scheduling to minimize work-in-process, earliness and tardiness costs

Our research is motivated by a scenario of a manufacturing company receiving highly customized orders from different customers. A good production schedule is required to complete the orders on time with the limited resources and minimize the relevant costs. Such a scenario is modelled as a job shop problem with non-regular performance measure (shorted as JIT-JSP). The objective of JIT-JSP is to minimize three inventory related costs: Work in process (WIP) holding, earliness and tardiness cost.Schedule generation procedures including idle time insertion are studied to generate feasible schedule for JIT-JSP. A modified tabu search algorithm (MTS) is developed to improve the schedule quality by searching the neighborhood for better schedules iteratively. A dispatching rule selector based on neural network is developed to solve the performance fluctuation of dispatching rules. Computational results show that the proposed procedures significantly improve the schedule quality.

Author dc:creator

• ZHU ZHECHENG

• job shop scheduling, just in time, schedule generation procedure, idle time insertion, tabu search, dispatching rule selector