A hybrid GRASP-VNS for Ship Routing and Scheduling Problem with Discretized Time Windows

Armas, Jesica de; Lalla-Ruiz, Eduardo; Exp�sito-Izquierdo, Christopher; Landa-Silva, Dario; Meli�n-Batista, Bel�n

Abstract

This paper addresses the Ship Routing and Scheduling Problem with Discretized Time Windows. Being one of the most relevant and challenging problems faced by decision makers from shipping companies, this tramp shipping problem lies in determining the set of contracts that should be served by each ship and the time windows that ships should use to serve each contract, with the aim of minimizing total costs. The use of discretized time windows allows for the consideration of a broad variety of features and practical constraints in a simple way. In order to solve this problem we propose a hybridazation of a Greedy Randomized Adaptive Search Procedure and a Variable Neighborhood Search, which improves previous heuristics results found in literature and requires very short computational time. Moreover, this algorithm is able to achieve the optimal results for many instances, demonstrating its good performance.

Citation

Armas, J. D., Lalla-Ruiz, E., Expósito-Izquierdo, C., Landa-Silva, D., & Melián-Batista, B. (2015). A hybrid GRASP-VNS for Ship Routing and Scheduling Problem with Discretized Time Windows. Engineering Applications of Artificial Intelligence, 45, https://doi.org/10.1016/j.engappai.2015.07.013

• Journal Article Type: Article
• Publication Date: Oct 1, 2015
• Deposit Date: Jan 21, 2016
• Publicly Available Date: Jan 21, 2016
• Journal: Engineering Applications of Artificial Intelligence
• Print ISSN: 0952-1976
• Electronic ISSN: 0952-1976
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 45
• DOI: https://doi.org/10.1016/j.engappai.2015.07.013
• Keywords: Vehicle Routing, Scheduling and Timetabling, Hybrid Metaheuristics, Grasp Algorithm, Variable Neighbourhood Search
• Public URL: https://nottingham-repository.worktribe.com/output/981672
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S0952197615001608