Parallel machine scheduling problem to minimize the earliness/tardiness costs with learning effect and deteriorating jobs

Authors:
M. Duran Toksarı;Ertan Güner
Affiliations:
Industrial Engineering Department, Erciyes University, Kayseri, Turkey;Industrial Engineering Department, Gazi University, Ankara, Turkey
Venue:
Journal of Intelligent Manufacturing
Year:
2010

Citing 13
Cited 3

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Flow shop scheduling problems with decreasing linear deterioration under dominant machines

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Heuristic algorithms for unrelated parallel machine scheduling with a common due date, release dates, and linear earliness and tardiness penalties

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A branch and bound algorithm for minimizing makespan on a single machine with unequal release times under learning effect and deteriorating jobs

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A hybrid memetic algorithm for maximizing the weighted number of just-in-time jobs on unrelated parallel machines

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Ant colony algorithms for a two-agent scheduling with sum-of processing times-based learning and deteriorating considerations

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Abstract

The focus of this work is to analyze parallel machine earliness/tardiness (ET) scheduling problem with simultaneous effects of learning and linear deterioration, sequence-dependent setups, and a common due-date for all jobs. By the effects of learning and linear deterioration, we mean that the processing time of a job is defined by an increasing function of its starting time and a decreasing function of the position in the sequence. We develop a mixed integer programming formulation for the problem and show that the optimal sequence is V-shaped: all jobs scheduled before the shortest jobs and all jobs scheduled after the shortest job are in a non-increasing and non-decreasing order of processing times, respectively. The developed model allows sequence-dependent setups and sequence-dependent early/tardy penalties. The illustrative example with 11 jobs for 2 machines and 3 machines shows that the model can easily provide the optimal solution, which is V-shaped, for problem.