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An Adapted Version of the Water Wave Optimization Algorithm for the Capacitated Vehicle Routing Problem with Time Windows with Application to a Real Case Using Probe Data

Author

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  • Letizia Tebaldi

    (Department of Engineering and Architecture, University of Parma, viale delle Scienze 181/A, 43124 Parma, Italy)

  • Teresa Murino

    (Department of Chemical, Materials and Industrial Production Engineering, University of Naples “Federico II”, Piazzale Tecchio 80, 80125 Napoli, Italy)

  • Eleonora Bottani

    (Department of Engineering and Architecture, University of Parma, viale delle Scienze 181/A, 43124 Parma, Italy)

Abstract

Customers’ habits, as far as shipping requests are concerned, have changed in the last decade, due to the fast spread of e-commerce and business to consumer (B2C) systems, thus generating more and more vehicles on the road, traffic congestion and, consequently, more pollution. Trying to partially solve this problem, the operational research field dedicates part of its research to possible ways to optimize transports in terms of costs, travel times, full loads etc., with the aim of reducing inefficiencies and impacts on profit, planet and people, i.e., the well-known triple bottom line approach to sustainability, also thanks to new technologies able to instantly provide probe data, which can detail information as far as the vehicle behavior. In line with this, an adapted version of the metaheuristic water wave optimization algorithm is here presented and applied to the context of the capacitated vehicle routing problem with time windows. This latter one is a particular case of the vehicle routing problem, whose aim is to define the best route in terms of travel time for visiting a set of customers, given the vehicles capacity and time constraints in which some customers need to be visited. The algorithm is then tested on a real case study of an express courier operating in the South of Italy. A nearest neighbor heuristic is applied, as well, to the same set of data, to test the effectiveness and accuracy of the algorithm. Results show a better performance of the proposed metaheuristic, which could improve the journeys by reducing the travel time by up to 23.64%.

Suggested Citation

  • Letizia Tebaldi & Teresa Murino & Eleonora Bottani, 2020. "An Adapted Version of the Water Wave Optimization Algorithm for the Capacitated Vehicle Routing Problem with Time Windows with Application to a Real Case Using Probe Data," Sustainability, MDPI, vol. 12(9), pages 1-13, May.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:9:p:3666-:d:353063
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    1. Richard Pomfret, 2011. "Trade and Transport in Central Asia," Book Chapters, in: Werner Hermann & Johannes F. Linn (ed.), Central Asia and the Caucasus: At the Crossroads of Eurasia in the 21st Century, chapter 3, pages 43–62, Emerging Markets Forum.
    2. Mishchenko S. P., 2011. "Economic security of rail transport," Вісник економіки транспорту і промисловості, CyberLeninka;Украинская государственная академия железнодорожного транспорта, issue 34, pages 206-209.
    3. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    4. Kalinichenko L. L., 2011. "Innovation policy railway transport of Ukraine," Вісник економіки транспорту і промисловості, CyberLeninka;Украинская государственная академия железнодорожного транспорта, issue 36, pages 314-318.
    5. Itf, 2011. "Meeting Society's Transport Needs under Tight Budgets," International Transport Forum Discussion Papers 2011/10, OECD Publishing.
    6. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    7. Kucheruk G. Y., 2011. "Place of transportation services in logistics systems," Вісник економіки транспорту і промисловості, CyberLeninka;Украинская государственная академия железнодорожного транспорта, issue 36, pages 66-71.
    8. Todd Litman & David Burwell, 2006. "Issues in sustainable transportation," International Journal of Global Environmental Issues, Inderscience Enterprises Ltd, vol. 6(4), pages 331-347.
    9. Baldacci, Roberto & Mingozzi, Aristide & Roberti, Roberto, 2012. "Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints," European Journal of Operational Research, Elsevier, vol. 218(1), pages 1-6.
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