Incremental LNS framework for integrated production, inventory, and vessel scheduling: Application to a global supply chain

Er Raqabi El Mehdi, Himmich Ilyas, El Hachemi Nizar, El Hallaoui Issmaïl and Soumis François

Omega, 2023, vol. 116, issue C

Abstract: This paper presents a multiobjective, mixed-integer linear programming (MILP) model that integrates production scheduling, inventory management, and vessel assignment for a global supply chain. Given that such large-scale problems are NP-hard and usually suffer from symmetry, we conduct an exploratory analysis to identify complexity sources. Following this, we design a novel variant of the large neighborhood search metaheuristic to tackle the problem efficiently. While symmetry is considered an issue in the literature, the implemented algorithm provides a practical way of profiting from instead of breaking it. Computationally, we reach near-optimal solutions in real-world instances. Compared to the default CPLEX and a reference algorithm that mimics real life, we gain significantly in terms of time, quality, and the number of feasible integer solutions found during the solving process. In addition to efficiency, integrated optimization enhances operations management capabilities and supply chain resilience.

Keywords: Large-scale optimization; MILP; Multiobjective optimization; Metaheuristics; Symmetry; Global supply chain (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305048322002274
Full text for ScienceDirect subscribers only

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:eee:jomega:v:116:y:2023:i:c:s0305048322002274

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.omega.2022.102821

Access Statistics for this article

Omega is currently edited by B. Lev

More articles in Omega from Elsevier
Bibliographic data for series maintained by Catherine Liu ().