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A bi-criteria evolutionary algorithm for a constrained multi-depot vehicle routing problem

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Abstract

Most research about the vehicle routing problem (VRP) does not collectively address many of the constraints that real-world transportation companies have regarding route assignments. Consequently, our primary objective is to explore solutions for real-world VRPs with a heterogeneous fleet of vehicles, multi-depot subcontractors (drivers), and pickup/delivery time window and location constraints. We use a nested bi-criteria genetic algorithm (GA) to minimize the total time to complete all jobs with the fewest number of route drivers. Our model will explore the issue of weighting the objectives (total time vs. number of drivers) and provide Pareto front solutions that can be used to make decisions on a case-by-case basis. Three different real-world data sets were used to compare the results of our GA vs. transportation field experts’ job assignments. For the three data sets, all 21 Pareto efficient solutions yielded improved overall job completion times. In 57 % (12/21) of the cases, the Pareto efficient solutions also utilized fewer drivers than the field experts’ job allocation strategies.

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Authors and Affiliations

  1. Jacksonville University, 2800 University Blvd N, Jacksonville, FL, USA

    Vikas Agrawal

  2. Fayetteville State University, 1200 Murchison Rd., Fayetteville, NC, USA

    Constance Lightner

  3. Clayton State University, 2000 Clayton State Boulevard, Morrow, GA, USA

    Carin Lightner-Laws

  4. MIT Lincoln Laboratory, 244 Wood St., Lexington, MA, USA

    Neal Wagner

Authors
  1. Vikas Agrawal
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  2. Constance Lightner
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  3. Carin Lightner-Laws
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  4. Neal Wagner
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Corresponding author

Correspondence to Carin Lightner-Laws.

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The authors declare that they have no conflict of interest.

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Communicated by V. Loia.

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Agrawal, V., Lightner, C., Lightner-Laws, C. et al. A bi-criteria evolutionary algorithm for a constrained multi-depot vehicle routing problem. Soft Comput 21, 5159–5178 (2017). https://doi.org/10.1007/s00500-016-2112-3

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