Issue |
RAIRO-Oper. Res.
Volume 55, Number 3, May-June 2021
|
|
---|---|---|
Page(s) | 1501 - 1522 | |
DOI | https://doi.org/10.1051/ro/2021062 | |
Published online | 08 June 2021 |
Efficient algorithms to minimize makespan of the unrelated parallel batch-processing machines scheduling problem with unequal job ready times
1
Department of Industrial Engineering, Mazandaran University of Science and Technology Babol, Mazandaran, Iran
2
Department of Rail Transportation Engineering, School of Railway Engineering, Iran University of Science and Technology, Tehran, Iran
* Corresponding author: y.zaruk89.ac@gmail.com
Received:
16
April
2020
Accepted:
17
April
2021
This paper considers the minimization of makespan in the unrelated parallel batch processing machines scheduling problem with considering non-identical job size and dynamic job ready time. The considered unrelated machines have different capacity and different processing speed. Each machine processes a number of the jobs as a batch at the same time so that the machine’s capacity is not exceeded. The batch processing time and the batch ready time are equal to the largest processing time and the largest ready time of jobs in the same batch, respectively. In this paper, a Mixed Integer Linear Programming (MILP) model, two categories of the heuristic procedures (six heuristics) and a meta-heuristic algorithm are proposed to solve the problem. A lower bound is also presented by relaxing of the original problem to evaluate the quality of the proposed algorithms. The computational experiments show the performance of the proposed algorithms under the considered measures.
Mathematics Subject Classification: 90B35 / 90C11 / 68W25
Key words: Unrelated parallel machines / batch-processing / heuristic / dynamic job ready times / Makespan / mathematical modeling
© The authors. Published by EDP Sciences, ROADEF, SMAI 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.