A hybrid adaptive large neighbourhood search algorithm for the capacitated location routing problem. (15th April 2021)

• Record Type: Journal Article
• Authors: Şatir Akpunar, Özge; Akpinar, Şener
• Is Part Of: Expert systems with applications. Volume 168(2021)
• Publication Date: 2021-04-15
• Subjects: Location routing problem -- Hybrid metaheuristic -- Adaptive large neighbourhood search -- Variable neighbourhood search; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.114304
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: This paper proposes a new hybrid metaheuristic algorithm that is composed of the adaptive large neighbourhood search (ALNS) and the variable neighbourhood search (VNS) algorithms to tackle the location routing problem (LRP) with capacity constraints. The rationale of the proposed hybrid metaheuristic algorithm is to enhance the performance of the ALNS algorithm by incorporating the VNS algorithm as an elitist local search. Therefore, the diversification and intensification strategies of the proposed hybrid metaheuristic algorithm are realized via the ALNS and VNS algorithms, respectively. The performance evaluation tests of the proposed hybrid metaheuristic algorithm are performed on the three classical LRP benchmark sets taken from the related literature, and the obtained results are compared against some of the formerly proposed and published methods in terms of solution quality. Computational results indicate that the proposed hybrid metaheuristic algorithm has a satisfactory performance in solving the LRP instances and is a competitive algorithm. Highlights: We proposed a hybrid ALNS algorithm for LRP. We hybridized ALNS via VNS. The performance of the proposed algorithm was tested on a set of benchmark instances. The results confirm the satisfactory performance of the algorithm in terms provided results.