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A Single-Machine Two-Agent Scheduling Problem By Ga Approach

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  • SHUENN-REN CHENG

    (Graduate Institute of Business Administration, Cheng Shiu University, Kaohsiung County, Taiwan)

Abstract

A single-machine two-agent scheduling problem with a truncation learning effect is being addressed in the study. The truncation learning effect means that the actual processing time of a job is a function of the sum of processing times of already scheduled jobs and a control parameter. The aim is to find an optimal schedule to minimize the total weighted completion time of jobs of the first agent under the circumstances that no tardy job is allowed for the second agent. A branch-and-bound and three heuristic-based genetic algorithms (GAs) are proposed to solve the problem. Also presented in the study are the computational results of all proposed algorithms.

Suggested Citation

  • Shuenn-Ren Cheng, 2012. "A Single-Machine Two-Agent Scheduling Problem By Ga Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 29(02), pages 1-22.
    • Handle: RePEc:wsi:apjorx:v:29:y:2012:i:02:n:s0217595912500133
    DOI: 10.1142/S0217595912500133
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    References listed on IDEAS

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    1. Alfons Oude Lansink & Arno Van Der Vlist, 2008. "Non‐Parametric Modelling of CO2 Emission Quota," Journal of Agricultural Economics, Wiley Blackwell, vol. 59(3), pages 487-497, September.
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    Cited by:

    1. Cheng, Shuenn-Ren, 2014. "Some new problems on two-agent scheduling to minimize the earliness costs," International Journal of Production Economics, Elsevier, vol. 156(C), pages 24-30.
    2. Shang-Chia Liu & Jiahui Duan & Win-Chin Lin & Wen-Hsiang Wu & Jan-Yee Kung & Hau Chen & Chin-Chia Wu, 2018. "A Branch-and-Bound Algorithm for Two-Agent Scheduling with Learning Effect and Late Work Criterion," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(05), pages 1-24, October.

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