Synchronizing production and delivery in flow shops with time-of-use electricity pricing

Humyun Fuad Rahman (), Tom Servranckx (), Ripon K. Chakrabortty (), Mario Vanhoucke () and Sondoss El Sawah ()
Additional contact information
Humyun Fuad Rahman: Newcastle University
Tom Servranckx: Ghent University
Ripon K. Chakrabortty: University of New South Wales
Mario Vanhoucke: Ghent University
Sondoss El Sawah: University of New South Wales

Annals of Operations Research, 2025, vol. 345, issue 1, No 13, 403 pages

Abstract: Abstract Manufacturing supply chains (SC) shift from traditional make-to-stock systems to make-to-order (MTO) systems in order to coordinate the production and distribution of complex and highly customized products. Despite the need for advanced scheduling approaches when coordinating such MTO-based SCs, there is little research focussing on practical settings that include variable processing speeds, sequence-dependent setup times (SDST) and time-of-use (TOU) electricity prices. However, these settings are important since they influence the energy consumption and the associated electricity costs have an impact on the decision-making process. Furthermore, there is also an increasing concern regarding green production in manufacturing such that the energy consumption cannot be ignored in decision making. In this study, we investigate a bi-objective energy-efficient permutation flow shop scheduling problem in MTO-based SC (EPFSPSC) with the conjoint objectives of minimising the cost of inventory, delivery, tardiness and electricity costs for production. In order to solve this problem, a genetic algorithm-based memetic algorithm is proposed and its effectiveness is demonstrated against a well-known benchmark approach. This research aims to assist production managers in making integrated production and distribution decisions, while simultaneously considering all associated costs and ensuring green manufacturing.

Keywords: Flow shop scheduling; Supply chain; Batch delivery; Electricity tariff; Memetic algorithm (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-024-06430-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:345:y:2025:i:1:d:10.1007_s10479-024-06430-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-024-06430-6

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().