Solving a two-agent single-machine scheduling problem considering learning effect

Authors:
Der-Chiang Li;Peng-Hsiang Hsu
Affiliations:
Department of Industrial and Information Management, National Cheng Kung University, No. 1, University Road, Tainan City 70101, Taiwan, ROC;Department of Industrial and Information Management, National Cheng Kung University, No. 1, University Road, Tainan City 70101, Taiwan, ROC and Department of Business Administration, Kang-Ning Jun ...
Venue:
Computers and Operations Research
Year:
2012

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Abstract

Scheduling with multiple agents and learning effect has drawn much attention. In this paper, we investigate the job scheduling problem of two agents competing for the usage of a common single machine with learning effect. The objective is to minimize the total weighted completion time of both agents with the restriction that the makespan of either agent cannot exceed an upper bound. In order to solve this problem we develop several dominance properties and a lower bound based on a branch-and-bound to find the optimal algorithm, and derive genetic algorithm based procedures for finding near-optimal solutions. The performances of the proposed algorithms are evaluated and compared via computational experiments.