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Boosting sustainable development goals: a hybrid metaheuristic approach for the heterogeneous vehicle routing problem with three-dimensional packing constraints and fuel consumption

  • S.I.: OR for Sustainability in Supply Chain Management
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Abstract

Due to rising carbon dioxide emissions and recent climate change events, there is an increasing focus on adopting Sustainable Road Freight Transportation to minimize fuel consumption. These issues are reflected in more recent research findings on adopting sustainable road transport methods in recent years, which positively affect the Sustainable Development Goals. This paper introduces the heterogeneous vehicle routing problem with three-dimensional packing constraints and environmental impact based on fuel consumption (3L-FHFVRP), an extension of the heterogeneous vehicle routing problem with 3D loading constraints (3L-HFVRP), considering fuel consumption as the objective function. We are given a set of requests and a heterogeneous fleet of vehicles. A set of minimum fuel consumption routes must be determined to transport each request from a loading site to the corresponding unloading site. In the 3L-FHFVRP, the customers’ demand is represented by a set of 3D rectangular items (boxes), and a 3D loading space considers the vehicle's capacity. This study introduces the 3L-FHFVRP and its details, as well as a procedure for solving it has been proposed. We propose a variable neighborhood search metaheuristic algorithm to solve the problem, and we show that it is proper for some variants. The proposed method considers three-dimensional packing constraints, heterogeneous vehicle fleets, and environmental impacts based on fuel consumption. The split coding for the well-known CVRP guarantees capacity and packing constraints. A GRASP scheme is proposed to evaluate the packing constraints of the heterogeneous fleet. The optimization scheme includes the environmental impact as a fuel consumption factor directly affecting the cost function. The efficiency of the proposed approach was tested on a set of benchmarking instances for 3L-FHFVRP, 3L-HFVRP, 3L-CVRP, 2L-FHFVRP, and 2L-HFVRP. The proposed algorithm is compared with the best-known results of the literature showing that it outperforms some of the previously published results within short computing times. In future work, it is proposed to consider practical constraints such as limited vehicle fleet and time windows within the problem and to enhance the improvement operators by adding search aspects in granular space.

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We want to acknowledge two anonymous referees for their valuable comments to improve the original version of our paper.

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  1. Department of Industrial Engineering, Universidad de Los Andes, Bogotá, Colombia

    Juan Esteban Rojas-Saavedra & David Álvarez-Martínez

  2. Department of Accounting and Finance, Universidad del Valle, Cali, Colombia

    John Willmer Escobar

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JERS, DÁM, and JWE: conceptualization, methodology; JERS, DÁM: software; JERS: data curation; DÁM and JWE: writing—original draft; JERS, DÁM, and JWE: writing—review and editing; JERS, DÁM, and JWE: visualization, investigation; DÁM and JWE: supervision.

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Rojas-Saavedra, J.E., Álvarez-Martínez, D. & Escobar, J.W. Boosting sustainable development goals: a hybrid metaheuristic approach for the heterogeneous vehicle routing problem with three-dimensional packing constraints and fuel consumption. Ann Oper Res (2023). https://doi.org/10.1007/s10479-023-05533-w

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