Less is more approach for competing groups scheduling with different learning effects

Baoyu Liao (), Xingming Wang, Xing Zhu, Shanlin Yang and Panos M. Pardalos
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Baoyu Liao: Hefei University of Technology
Xingming Wang: Hefei University of Technology
Xing Zhu: Hefei University of Technology
Shanlin Yang: Hefei University of Technology
Panos M. Pardalos: University of Florida

Journal of Combinatorial Optimization, 2020, vol. 39, issue 1, No 3, 33-54

Abstract: Abstract This paper investigates a two-competing group scheduling problem on serial-batching machines considering setup times and truncated job-dependent learning effects. The objective is to minimize the makespan of one group with truncated learning effect under the constraint that the makespan of the other group with general learning effect cannot exceed an upper bound. We propose some structural properties for the scheduling problem on a given machine, and design a Less-is-more-based iterative reference greedy algorithm for parallel machines scheduling problems. The computational results show that the proposed algorithm can solve the studied problems effectively.

Keywords: Competing groups scheduling; Less is more; Learning effect; Iterative reference greedy algorithm (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10878-019-00452-8

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