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Bi-objective collaborative electric vehicle routing problem: mathematical modeling and matheuristic approach

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Abstract

Due to increasing concern about the environmental impact of internal combustion engines, both companies and customers are inclined to much cleaner alternatives like electric vehicles. Moreover, to withstand the current competitive market, companies seek strategies like collaboration to reduce their operational costs and enhance their customer service level. In this regard, this paper investigates a collaborative capacitated electric vehicle routing problem (CoCEVRP). Two novel bi-objective mathematical models, including several real-world assumptions, are developed for the problem under collaborative and non-collaborative strategies. Since the problem is intractable, a matheuristic approach is devised based on the integration of the multi-objective Keshtel algorithm (MOKA) with a mathematical model. Finally, a comprehensive computational experiment is carried out to validate and assess the performance of the devised approach and examine the impact of collaboration among companies. According to the results, the MOKA demonstrates an auspicious performance to achieve high-quality solutions. Moreover, the collaborative strategy can lead to a significant reduction in the total cost and the total electrical energy consumption, as well as a considerable improvement in the customer service level and vehicle utilization.

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Authors and Affiliations

  1. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Behdin Vahedi-Nouri, Hamidreza Arbabi, Fariborz Jolai, Reza Tavakkoli-Moghaddam & Ali Bozorgi-Amiri

Authors
  1. Behdin Vahedi-Nouri
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  2. Hamidreza Arbabi
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  3. Fariborz Jolai
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  4. Reza Tavakkoli-Moghaddam
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  5. Ali Bozorgi-Amiri
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Contributions

The authors of this research entitled “Bi-objective collaborative electric vehicle routing problem: mathematical modeling and matheuristic approach” certify that all the co-authors have made substantial contributions to the reported work and had an active part in the subject matter or materials discussed in this manuscript. Furthermore, each author certifies that this material or similar material has not been and will not be submitted to or published in any other publication before its appearance in the “Journal of Ambient Intelligence and Humanized Computing”. Behdin Vahedi-Nouri: conceptualization, methodology, writing—original draft. Hamidreza Arbabi: methodology, software, visualization. Fariborz Jolai: supervision, project administration. Reza Tavakkoli-Moghaddam: resources, writing—review & editing. Ali Bozorgi-Amiri: data curation, validation.

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Correspondence to Reza Tavakkoli-Moghaddam.

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Vahedi-Nouri, B., Arbabi, H., Jolai, F. et al. Bi-objective collaborative electric vehicle routing problem: mathematical modeling and matheuristic approach. J Ambient Intell Human Comput 14, 10277–10297 (2023). https://doi.org/10.1007/s12652-021-03689-6

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