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An Ant Colony-Based Matheuristic Approach for Solving a Class of Vehicle Routing Problems

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Computational Logistics (ICCL 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9335))

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Abstract

We propose a matheuristic approach to solve several types of vehicle routing problems (VRP). In the VRP, a fleet of capacitated vehicles visits a set of customers exactly once to satisfy their demands while obeying problem specific characteristics and constraints such as homogeneous or heterogeneous fleet, customer service time windows, single or multiple depots. The proposed matheuristic is based on an ant colony optimization (ACO) algorithm which constructs good feasible solutions. The routes obtained in the ACO procedure are accumulated in a pool as columns which are then fed to an integer programming (IP) optimizer that solves the set-partitioning (-covering) formulation of the particular VRP. The (near-)optimal solution found by the solver is used to reinforce the pheromone trails in ACO. This feedback mechanism between the ACO and IP procedures helps the matheuristic better converge to high quality solutions. We test the performance of the proposed matheuristic on different VRP variants using well-known benchmark instances from the literature. Our computational experiments reveal competitive results: we report six new best solutions and meet the best-known solution in 120 instances out of 193.

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Authors and Affiliations

  1. School of Industrial Engineering, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands

    Umman Mahir Yıldırım

  2. Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Istanbul, Turkey

    Umman Mahir Yıldırım & Bülent Çatay

Authors
  1. Umman Mahir Yıldırım
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  2. Bülent Çatay
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Correspondence to Umman Mahir Yıldırım .

Editor information

Editors and Affiliations

  1. Delft University of Technology, Delft, The Netherlands

    Francesco Corman

  2. University of Hamburg, Hamburg, Germany

    Stefan Voß

  3. Delft University of Technology, Delft, The Netherlands

    Rudy R. Negenborn

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Yıldırım, U.M., Çatay, B. (2015). An Ant Colony-Based Matheuristic Approach for Solving a Class of Vehicle Routing Problems. In: Corman, F., Voß, S., Negenborn, R. (eds) Computational Logistics. ICCL 2015. Lecture Notes in Computer Science(), vol 9335. Springer, Cham. https://doi.org/10.1007/978-3-319-24264-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-24264-4_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24263-7

  • Online ISBN: 978-3-319-24264-4

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