A Simulated Annealing-based Optimization Approach for Integrated Process Planning and Scheduling
Résumé
A job shop needs to deal with a lot of make-to-order business, in which the orders are usually diverse in types but each one is small in volume. To increase the flexibility and responsiveness of the job shop in the more competitive market, process planning and scheduling modules have been actively developed and deployed. The functions of the two modules are usually complementary, and it is ideal to integrate them more tightly to achieve the global optimization of product development and manufacturing. In this paper, a unified representation model and a simulated annealing-based approach have been developed to facilitate the integration and optimization process. In the approach, three strategies, including processing flexibility, operation sequencing flexibility and scheduling flexibility, have been used for exploring the searching space to support the optimization process effectively. Performance criteria, such as makespan, the balanced level of machine utilization, job tardiness and manufacturing cost have been systematically defined to make the algorithm adaptive to meet various practical requirements. Through case studies under various working conditions, and the comparison of this approach with two modern evolutionary approaches, the merits and characteristics of the approach are highlighted.
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