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Urban hazmat transportation with multi-factor

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Abstract

In this paper, an urban hazmat transportation problem considering multiple factors that tangle with real-world applications (i.e., weather conditions, traffic conditions, population density, time window, link closure and half link closure) is investigated. Based on multiple depot capacitated vehicle routing problem, we provide a multi-level programming formulation for urban hazmat transportation. To obtain the Pareto optimal solution, an improved biogeography-based optimization (improved BBO) algorithm is designed, comparing with the original BBO and genetic algorithm, with both simulated numerical examples and a real-world case study, demonstrating the effectiveness of the proposed approach.

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Notes

  1. U.S. Department of Transportation. See at: https://www.transportation.gov.

  2. Electronic map of China petroleum and chemical corporation Beijing oil products company. See at: http://wap.bjoil.com/portal/map.jsp.

  3. Beijing traffic management bureau. See at: http://cgs.bjjtgl.gov.cn/roadpublish/Map/trafficOutNew1.jsp.

  4. Beijing meteorological service. See at: http://www.bjmb.gov.cn.

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Acknowledgements

This study was supported by grants from National Natural Science Foundation of China of No. 71722007, and the Fundamental Research Funds for the Central Universities (No. XK1802-5).

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Authors and Affiliations

  1. School of Economics and Management, Beijing University of Chemical Technology, Beijing, China

    Xiang Li

  2. Faculty of Science and Engineering, Hosei University, Tokyo, Japan

    Jiaoman Du & Lei Li

  3. Department of Computer Science, Aberystwyth University, Aberystwyth, UK

    Xiang Li & Changjing Shang

  4. Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, China

    Xiang Li

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  1. Jiaoman Du
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  2. Xiang Li
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  3. Lei Li
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  4. Changjing Shang
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Correspondence to Xiang Li.

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Du, J., Li, X., Li, L. et al. Urban hazmat transportation with multi-factor. Soft Comput 24, 6307–6328 (2020). https://doi.org/10.1007/s00500-019-03956-x

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