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Heuristics for Job Shop Scheduling Problems with Progressive Weighted Tardiness Penalties and Inter-machine Overlapping Sequence-dependent Setup Times

作者
Chatpon Mongkalig,Mario T. Tabucanon,Nguyen Van Hop
摘要

Abstract. This paper presents new scheduling heuristics, namely Mean Progressive Weighted Tardiness Estimator (MPWT) Heuristic Method and modified priority rules with sequence-dependent setup times consideration. These are designed to solve job shop scheduling problems with new performance measures – progressive weighted tardiness penalties. More realistic constraints, which are inter-machine overlapping sequencedependent setup times, are considered. In real production environments, inter-machine overlapping sequencedependent setups are significant. Therefore, modified scheduling generation algorithms of active and nondelay schedules for job shop problems with inter-machine overlapping sequence-dependent setup times are proposed in this paper. In addition, new customer-based measures of performance, which are total earliness and progressive weighted tardiness, and total progressive weighted tardiness, are proposed. The objective of the first experiment is to compare the proposed priority rules with the consideration of sequence-dependent setup times and the standard priority rules without setup times consideration. The results indicate that the proposed priority rules with setup times consideration are superior to the standard priority rules without the consideration of setup times. From the second experiment and the third experiment to compare the proposed MPWT heuristic approach with the efficient priority rules with setup times consideration, the MPWT heuristic method is significantly superior to the Batched Apparent Tardiness Cost with Sequence-dependent Setups (BATCS) rule, and other

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