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Online scheduling on parallel-batch machines with periodic availability constraints and job delivery

Author

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  • Lin, Ran
  • Wang, Jun-Qiang
  • Oulamara, Ammar

Abstract

We address an online scheduling problem on identical parallel-batch machines with periodic availability constraints and job delivery. A parallel-batch machine can process several jobs simultaneously in a batch without any preemption. The processing time of a batch is equal to the maximum processing time of the jobs in this batch, and the job processing times we consider are identical on all machines. Available and unavailable time intervals occur alternately on machines. The unavailable time intervals have the same start and end time on different machines. Jobs are released over time, which means that no information of the job is known in advance before its release date. After completion, job is delivered to customer. Three objective functions, namely, maximum flow time, maximum delivery time and total flow time are considered separately. For these objectives, we derive lower bounds on competitive ratios, provide online algorithms and analyze their competitive ratios.

Suggested Citation

  • Lin, Ran & Wang, Jun-Qiang & Oulamara, Ammar, 2023. "Online scheduling on parallel-batch machines with periodic availability constraints and job delivery," Omega, Elsevier, vol. 116(C).
    • Handle: RePEc:eee:jomega:v:116:y:2023:i:c:s0305048322002109
    DOI: 10.1016/j.omega.2022.102804
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    References listed on IDEAS

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    1. Zhijie Huang & Lin Huang & Debiao Li, 2024. "Co-Evolutionary Algorithm for Two-Stage Hybrid Flow Shop Scheduling Problem with Suspension Shifts," Mathematics, MDPI, vol. 12(16), pages 1-30, August.
    2. Lin, Ran & Wang, Jun-Qiang & Liu, Zhixin & Xu, Jun, 2023. "Best possible algorithms for online scheduling on identical batch machines with periodic pulse interruptions," European Journal of Operational Research, Elsevier, vol. 309(1), pages 53-64.

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