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A rich vehicle routing problem dealing with perishable food: a case study

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  • Pedro Amorim
  • Sophie Parragh
  • Fabrício Sperandio
  • Bernardo Almada-Lobo

Abstract

This paper presents a successful application of operations research techniques in guiding the decision making process to achieve a superior operational efficiency in core activities. We focus on a rich vehicle routing problem faced by a Portuguese food distribution company on a daily basis. This problem can be described as a heterogeneous fleet site dependent vehicle routing problem with multiple time windows. We use the adaptative large neighbourhood search framework, which has proven to be effective to solve a variety of different vehicle routing problems. Our plans are compared against those of the company and the impact that the proposed decision support tool may have in terms of cost savings is shown. The algorithm converges quickly giving the planner considerably more time to focus on value-added tasks, rather than manually correct the routing schedule. Moreover, contrarily to the necessary adaptation time of the planner, the tool is quite flexible in following market changes, such as the introduction of new customers or new products. Copyright Sociedad de Estadística e Investigación Operativa 2014

Suggested Citation

  • Pedro Amorim & Sophie Parragh & Fabrício Sperandio & Bernardo Almada-Lobo, 2014. "A rich vehicle routing problem dealing with perishable food: a case study," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 489-508, July.
    • Handle: RePEc:spr:topjnl:v:22:y:2014:i:2:p:489-508
    DOI: 10.1007/s11750-012-0266-4
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    References listed on IDEAS

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    1. Faulin, Javier, 2003. "Applying MIXALG procedure in a routing problem to optimize food product delivery," Omega, Elsevier, vol. 31(5), pages 387-395, October.
    2. 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.
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    Cited by:

    1. Puca Huachi Vaz Penna & Anand Subramanian & Luiz Satoru Ochi & Thibaut Vidal & Christian Prins, 2019. "A hybrid heuristic for a broad class of vehicle routing problems with heterogeneous fleet," Annals of Operations Research, Springer, vol. 273(1), pages 5-74, February.
    2. Ostermeier, Manuel, 2024. "The supply of convenience stores: Challenges of short-distance routing within the constraints of working time regulations," European Journal of Operational Research, Elsevier, vol. 314(3), pages 997-1012.
    3. Gaoyuan Qin & Fengming Tao & Lixia Li, 2019. "A Vehicle Routing Optimization Problem for Cold Chain Logistics Considering Customer Satisfaction and Carbon Emissions," IJERPH, MDPI, vol. 16(4), pages 1-17, February.
    4. Zhixue Zhao & Xiamiao Li & Xiancheng Zhou, 2020. "Optimization of transportation routing problem for fresh food in time-varying road network: Considering both food safety reliability and temperature control," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-19, July.
    5. Max Leyerer & Marc-Oliver Sonneberg & Maximilian Heumann & Tim Kammann & Michael H. Breitner, 2019. "Individually Optimized Commercial Road Transport: A Decision Support System for Customizable Routing Problems," Sustainability, MDPI, vol. 11(20), pages 1-21, October.
    6. Pedro L. Miranda & Reinaldo Morabito & Deisemara Ferreira, 2018. "Optimization model for a production, inventory, distribution and routing problem in small furniture companies," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 30-67, April.
    7. Siling Lu & Fan Zhou, 2024. "Impact of Ship Emission Control Area Policies on Port Air Quality—A Case Study of Ningbo Port, China," Sustainability, MDPI, vol. 16(9), pages 1-22, April.
    8. Jing Chen & Pengfei Gui & Tao Ding & Sanggyun Na & Yingtang Zhou, 2019. "Optimization of Transportation Routing Problem for Fresh Food by Improved Ant Colony Algorithm Based on Tabu Search," Sustainability, MDPI, vol. 11(23), pages 1-22, November.
    9. Coelho, V.N. & Grasas, A. & Ramalhinho, H. & Coelho, I.M. & Souza, M.J.F. & Cruz, R.C., 2016. "An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints," European Journal of Operational Research, Elsevier, vol. 250(2), pages 367-376.
    10. Danlian Li & Qian Cao & Min Zuo & Fei Xu, 2020. "Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm," Sustainability, MDPI, vol. 12(5), pages 1-17, March.
    11. Songyi Wang & Fengming Tao & Yuhe Shi & Haolin Wen, 2017. "Optimization of Vehicle Routing Problem with Time Windows for Cold Chain Logistics Based on Carbon Tax," Sustainability, MDPI, vol. 9(5), pages 1-23, April.
    12. Ehsan Khodabandeh & Lawrence V. Snyder & John Dennis & Joshua Hammond & Cody Wanless, 2022. "C.H. Robinson Uses Heuristics to Solve Rich Vehicle Routing Problems," Interfaces, INFORMS, vol. 52(2), pages 173-188, March.
    13. Kramer, Raphael & Cordeau, Jean-François & Iori, Manuel, 2019. "Rich vehicle routing with auxiliary depots and anticipated deliveries: An application to pharmaceutical distribution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 162-174.
    14. Hang Thi Thanh Vu & Jeonghan Ko, 2023. "Inventory Transshipment Considering Greenhouse Gas Emissions for Sustainable Cross-Filling in Cold Supply Chains," Sustainability, MDPI, vol. 15(9), pages 1-22, April.

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