Job shop scheduling for meeting due dates and minimizing overtime using genetic algorithm incorporating new priority rules

Abstract

This paper presents an efficient scheduling method for a job shop environment in which working shifts repeat regularly and production capacity is adjustable by adding overtime for each machine in each working shift. The primal objective of scheduling is to meet job due dates and the secondary one is to minimize total overtime. This problem is a highly complex one in which simultaneous decision making for operation sequencing and overtime usage is required to efficiently achieve the two objectives having a trade-off relationship. We have already proposed the method using genetic algorithm incorporating priority rule for this scheduling problem. In the method, priority rules for operation sequencing were the key for high performance. This paper improves the method by applying priority rules for both operation sequencing and overtime usage. For operation sequencing, a new priority rule called (SL/RPN) β+SPT is proposed. For the determination of overtime usage, a method using a critical-ratio-based rule is newly introduced. Numerical experiments show the effectiveness of the proposed method.