Differential Evolution Algorithm to Solve the Parallel Batch Processing Machine Scheduling Problem with Multiple Jobs

We conducted this study with the aim of resolving the scheduling problem of parallel batch processing machines (PBPM) with different capacity constraints and different energy consumption per unit of time, as well as jobs with different processing times, arrival times, delivery dates and sizes, with...

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Veröffentlicht in:Engineering proceedings 2023-09, Vol.45 (1), p.22
Hauptverfasser: Xue Zhao, Yarong Chen, Mudassar Rauf, Chen Wang
Format: Artikel
Sprache:eng
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Zusammenfassung:We conducted this study with the aim of resolving the scheduling problem of parallel batch processing machines (PBPM) with different capacity constraints and different energy consumption per unit of time, as well as jobs with different processing times, arrival times, delivery dates and sizes, with the goal of simultaneously minimizing the maximum completion time, ET and total energy consumption. The IUDRLM rule is used to batch and sort jobs, and a decomposition-based multi-objective differential evolution algorithm MODE/D is proposed. Simulation experiments are performed to compare the performance of the proposed algorithm to those of existing algorithms. The proposed MODE/D algorithm outperformed NSGA-III in terms of NR value (0.96) and IGD (6.6) measures.
ISSN:2673-4591
DOI:10.3390/engproc2023045022