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Scheduling orders on either dedicated or flexible machines in parallel to minimize total weighted completion time

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  • Joseph Leung
  • Haibing Li
  • Michael Pinedo

Abstract

We are interested in the problem of scheduling orders for different product types in a facility with a number of machines in parallel. Each order asks for certain amounts of various different product types which can be produced concurrently. Each product type can be produced on a subset of the machines. Two extreme cases of machine environments are of interest. In the first case, each product type can be produced on one and only one machine which is dedicated to that product type. In the second case, all machines are identical and flexible; each product type can be produced by any one of the machines. Moreover, when a machine in this case switches over from one product type to another, no setup is required. Each order has a release date and a weight. Preemptions are not allowed. The objective is minimizing the total weighted completion time of the orders. Even when all orders are available at time 0, both types of machine environments have been shown to be NP-hard for any fixed number (≥2) of machines. This paper focuses on the design and analysis of approximation algorithms for these two machine environments. We also present empirical comparisons of the various algorithms. The conclusions from the empirical analyses provide insights into the trade-offs with regard to solution quality, speed, and memory space. Copyright Springer Science+Business Media, LLC 2008

Suggested Citation

  • Joseph Leung & Haibing Li & Michael Pinedo, 2008. "Scheduling orders on either dedicated or flexible machines in parallel to minimize total weighted completion time," Annals of Operations Research, Springer, vol. 159(1), pages 107-123, March.
  • Handle: RePEc:spr:annopr:v:159:y:2008:i:1:p:107-123:10.1007/s10479-007-0270-5
    DOI: 10.1007/s10479-007-0270-5
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    References listed on IDEAS

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    1. Leung, Joseph Y.-T. & Li, Haibing & Pinedo, Michael, 2006. "Scheduling orders for multiple product types with due date related objectives," European Journal of Operational Research, Elsevier, vol. 168(2), pages 370-389, January.
    2. Leslie A. Hall & Andreas S. Schulz & David B. Shmoys & Joel Wein, 1997. "Scheduling to Minimize Average Completion Time: Off-Line and On-Line Approximation Algorithms," Mathematics of Operations Research, INFORMS, vol. 22(3), pages 513-544, August.
    3. Chang Sup Sung & Sang Hum Yoon, 1998. "Minimizing total weighted completion time at a pre-assembly stage composed of two feeding machines," International Journal of Production Economics, Elsevier, vol. 54(3), pages 247-255, May.
    4. James D. Blocher & Dilip Chhajed, 1996. "The customer order lead‐time problem on parallel machines," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(5), pages 629-654, August.
    5. Joseph Y‐T. Leung & Haibing Li & Michael Pinedo, 2006. "Approximation algorithms for minimizing total weighted completion time of orders on identical machines in parallel," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(4), pages 243-260, June.
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    Cited by:

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    4. Husam Dauod & Nieqing Cao & Debiao Li & Jaehee Kim & Sang Won Yoon & Daehan Won, 2023. "An Order Scheduling Heuristic to Minimize the Total Collation Delays and the Makespan in High-Throughput Make-to-Order Manufacturing Systems," SN Operations Research Forum, Springer, vol. 4(2), pages 1-23, June.
    5. Lee, Ik Sun, 2013. "Minimizing total tardiness for the order scheduling problem," International Journal of Production Economics, Elsevier, vol. 144(1), pages 128-134.
    6. Lung-Yu Li & Jian-You Xu & Shuenn-Ren Cheng & Xingong Zhang & Win-Chin Lin & Jia-Cheng Lin & Zong-Lin Wu & Chin-Chia Wu, 2022. "A Genetic Hyper-Heuristic for an Order Scheduling Problem with Two Scenario-Dependent Parameters in a Parallel-Machine Environment," Mathematics, MDPI, vol. 10(21), pages 1-22, November.
    7. Framinan, Jose M. & Perez-Gonzalez, Paz & Fernandez-Viagas, Victor, 2019. "Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures," European Journal of Operational Research, Elsevier, vol. 273(2), pages 401-417.
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