Title: An efficient heuristic algorithm for flow shop scheduling problem with periodic machine specific halting and preventive maintenance operations

Authors: M. Thangaraj; Thenepalle Jayanth Kumar

Addresses: Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Chennai – 600127, India ' Department of Mathematics, Faculty of Engineering and Technology, JAIN (Deemed-to-be-University), Kanakapura, 562112, Karnataka, India

Abstract: In the majority of flow shop scheduling scenarios, machine availability is typically assumed consistent throughout the process. Allowing machines to operate continually without a break, however, results decline in productivity or machine failure. Therefore, it is required to allow machines to undergo maintenance operations periodically including halts to avoid machine breakdowns as well as improve performance factors like productivity, reliability and affordability. The existing literature lacks comprehensive studies on flow shop scheduling models integrated with halting times and preventive maintenance operations. Given the practical relevance of this gap, this paper first address a flow shop scheduling problem (FSSP) with periodic machine-specific halting and preventive maintenance operations. To minimise the overall tardiness and effectively manage halting and preventive maintenance operations with job scheduling, an effective NEH-based heuristic algorithm has been developed. As the present problem is new to the literature, comparative studies are not carried out. However, over 50 Taillard benchmark instances ranging from 20-jobs five-machines to 200-jobs ten-machines are used to test the performance of the proposed technique and results are duly reported, which could be helpful as a comparative basis for further research. The results reveal that the proposed algorithm provides the best solutions within a considerable time.

Keywords: flow shop scheduling problem; FSSP; halting operations; NEH algorithm; preventive maintenance; Taillard instances.

DOI: 10.1504/IJSOM.2025.149975

International Journal of Services and Operations Management, 2025 Vol.52 No.3, pp.275 - 292

Received: 17 Feb 2023
Accepted: 24 Aug 2023
Published online: 20 Nov 2025 *

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