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Order acceptance and scheduling with earliness and tardiness penalties

Author

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  • Simon Thevenin

    (University of Geneva)

  • Nicolas Zufferey

    (University of Geneva)

  • Marino Widmer

    (University of Fribourg)

Abstract

This paper addresses a production scheduling problem in a single-machine environment, where a job can be either early, on time, late, or rejected. In order acceptance and scheduling contexts, it is assumed that the production capacity of a company is overloaded. The problem is therefore to decide which orders to accept and how to sequence their production. In contrast with the existing literature, the considered problem jointly takes into account the following features: earliness and tardiness penalties (which can be linear or quadratic), sequence-dependent setup times and costs, rejection penalties, and the possibility of having idle times. The practical relevance of this new NP-hard problem is discussed and various solution methods are proposed, ranging from a basic greedy algorithm to refined metaheuristics (e.g., tabu search, the adaptive memory algorithm, population-based approaches loosely inspired on ant algorithms). The methods are compared for instances with various structures containing up to 200 jobs. For small linear instances, the metaheuristics are favorably compared with an exact formulation using CPLEX 12.2. Managerial insights and recommendations are finally given.

Suggested Citation

  • Simon Thevenin & Nicolas Zufferey & Marino Widmer, 2016. "Order acceptance and scheduling with earliness and tardiness penalties," Journal of Heuristics, Springer, vol. 22(6), pages 849-890, December.
    • Handle: RePEc:spr:joheur:v:22:y:2016:i:6:d:10.1007_s10732-016-9321-x
    DOI: 10.1007/s10732-016-9321-x
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    References listed on IDEAS

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    Cited by:

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    2. Mohamadreza Dabiri & Mehdi Yazdani & Bahman Naderi & Hassan Haleh, 2022. "Modeling and solution methods for hybrid flow shop scheduling problem with job rejection," Operational Research, Springer, vol. 22(3), pages 2721-2765, July.
    3. Li, Xin & Ventura, Jose A., 2020. "Exact algorithms for a joint order acceptance and scheduling problem," International Journal of Production Economics, Elsevier, vol. 223(C).
    4. Naderi, Bahman & Roshanaei, Vahid, 2020. "Branch-Relax-and-Check: A tractable decomposition method for order acceptance and identical parallel machine scheduling," European Journal of Operational Research, Elsevier, vol. 286(3), pages 811-827.
    5. Joonyup Eun & Chang Sup Sung & Eun-Seok Kim, 2017. "Maximizing total job value on a single machine with job selection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 998-1005, September.

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