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Some new problems on two-agent scheduling to minimize the earliness costs

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  • Cheng, Shuenn-Ren

Abstract

We consider several two-agent scheduling problems, where agents A and B have to share a single machine while processing their jobs. The objective is to minimize a certain objective function which depends on the completion time of all the jobs, while keeping the objective of agent B (with regard to its jobs only) below or at a fixed level Q. Specifically, we focus on minimizing certain objective functions of all the jobs such as maximum earliness cost, total weighted earliness cost, and total weighted earliness and tardiness cost, subject to an upper bound on a certain objective function of agent B. We introduce polynomial time solution for the maximum earliness cost problem, and prove NP-hardness for the total weighted earliness cost and total weighted earliness and tardiness cost cases. We also discuss some polynomially solvable cases for the total weighted earliness cost problem.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:156:y:2014:i:c:p:24-30
    DOI: 10.1016/j.ijpe.2014.05.004
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    Cited by:

    1. Enrique Gerstl & Baruch Mor & Gur Mosheiov, 2017. "Scheduling with two competing agents to minimize total weighted earliness," Annals of Operations Research, Springer, vol. 253(1), pages 227-245, June.
    2. Wang, Du-Juan & Yin, Yunqiang & Xu, Jianyou & Wu, Wen-Hsiang & Cheng, Shuenn-Ren & Wu, Chin-Chia, 2015. "Some due date determination scheduling problems with two agents on a single machine," International Journal of Production Economics, Elsevier, vol. 168(C), pages 81-90.
    3. Xiaoling Cao & Wen-Hsing Wu & Wen-Hung Wu & Chin-Chia Wu, 2018. "Some two-agent single-machine scheduling problems to minimize minmax and minsum of completion times," Operational Research, Springer, vol. 18(2), pages 293-314, July.

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