Cariou, Pierre, Cheaitou, Ali, Larbi, Rim, Hamdan, Sadeque (2018) Liner shipping network design with emission control areas: A genetic algorithm-based approach. Transportation Research Part D: Transport and Environment, 63 . pp. 604-621. ISSN 1361-9209. (doi:10.1016/j.trd.2018.06.020) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:90729)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) | |
Official URL: http://dx.doi.org/10.1016/j.trd.2018.06.020 |
Abstract
To curb emissions, containerized shipping lines face the traditional trade-off between cost and emissions (CO2 and SOx) reduction. This paper considers this element in the context of liner service design and proposes a mixed integer linear programming (MILP) model based on a multi-commodity pickup and delivery arc-flow formulation. The objective is to maximize the profit by selecting the ports to be visited, the sequence of port visit, the cargo flows between ports, as well as the number/operating speeds of vessels on each arc of the selected route. The problem also considers that Emission Control Areas (ECAs) exist in the liner network and accounts for the vessel carrying capacity. In addition to using the MILP solver of CPLEX, we develop in the paper a specific genetic algorithm (GA) based heuristic and show that it gives the possibility to reach an optimal solution when solving large size instances. © 2018 Elsevier Ltd
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.trd.2018.06.020 |
Uncontrolled keywords: | Carbon dioxide; Economic and social effects; Electronic trading; Emission control; Genetic algorithms; Ships; Strain measurement, Arc flow; Liner service; Mixed integer linear programming (MILP); Mixed integer linear programming model; Multi-commodity; Optimal solutions; Optimum speed; Pickup and delivery, Integer programming, carbon monoxide; design; emission control; genetic algorithm; linear programing; numerical model; shipping; sulfur compound |
Subjects: | H Social Sciences |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Sadeque Hamdan |
Date Deposited: | 09 Nov 2021 14:37 UTC |
Last Modified: | 05 Nov 2024 12:56 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/90729 (The current URI for this page, for reference purposes) |
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