A hybrid matheuristic for the Two-Stage Capacitated Facility Location problem
•A new hybrid matheuristic for the Two-Stage Capacitated Facility Location problem.•CS is combined with ALNS and Local Branching for the first time in the literature.•Set of benchmark instances were used in the experiments.•State-of-art methods are outperformed in both quality and time.•New best sol...
Gespeichert in:
Veröffentlicht in: | Expert systems with applications 2021-12, Vol.185, p.115501, Article 115501 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | •A new hybrid matheuristic for the Two-Stage Capacitated Facility Location problem.•CS is combined with ALNS and Local Branching for the first time in the literature.•Set of benchmark instances were used in the experiments.•State-of-art methods are outperformed in both quality and time.•New best solutions for the TSCFL are reported.
In the class of supply chain problems, the Two-Stage Capacitated Facility Location (TSCFL) is defined by optimal locations for installing factories and warehouses to meet the demand of customers. The problem aims to minimize operating costs: opening facilities and the flow of products from factories to customers, passing through warehouses, meeting the capacity constraints of factories and warehouses and customers’ demand. To solve this problem, a hybridization of Clustering Search (CS), Adaptive Large Neighborhood Search (ALNS) and Local Branching (LB) is proposed. This hybridization is a new and interesting approach which has found high quality solutions in low computational time. To show that, computational experiments were performed using benchmark instances. The results showed that the proposed method outperforms the current state-of-art for the TSCFL for 40 out of 50 instances. |
---|---|
ISSN: | 0957-4174 1873-6793 |
DOI: | 10.1016/j.eswa.2021.115501 |