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Energy-efficient frozen food transports: the Refrigerated Routing Problem

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  • Antonella Meneghetti
  • Sara Ceschia

Abstract

Given the growing importance of cold chains and the need to promote sustainable processes, energy efficiency in refrigerated transports is investigated at operational level. The Refrigerated Routing Problem is defined, involving multi-drop deliveries of palletised unit loads of frozen food from a central depot to clients. The objective is to select the route with minimum fuel consumption for both traction and refrigeration. The problem formulation considers speed variation due to traffic congestion phenomena, as well as decreasing load on board along the route as successive clients are visited. Transmission load for exposure of the vehicle to outdoor temperatures and infiltration load at door opening are modelled, taking into account outdoor conditions varying along the day and the year. The resulting multi-period problem is modelled and solved by means of Constraint Programming. Test scenarios come from a real local network for frozen bread dough distributed to supermarkets. Results show how fuel minimisation leads to the selection of different routes in comparison to the traditional total travel distance or time objectives. Energy savings are affected by demand distribution among the clients, departure time, number of visits per tour, seasonality and location of the delivery network.

Suggested Citation

  • Antonella Meneghetti & Sara Ceschia, 2020. "Energy-efficient frozen food transports: the Refrigerated Routing Problem," International Journal of Production Research, Taylor & Francis Journals, vol. 58(14), pages 4164-4181, July.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:14:p:4164-4181
    DOI: 10.1080/00207543.2019.1640407
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    Cited by:

    1. Isabel Cerrillo & Pablo Saralegui-Díez & Rubén Morilla-Romero-de-la-Osa & Manuel González de Molina & Gloria I. Guzmán, 2023. "Nutritional Analysis of the Spanish Population: A New Approach Using Public Data on Consumption," IJERPH, MDPI, vol. 20(2), pages 1-15, January.
    2. Angelo Maiorino & Adrián Mota-Babiloni & Fabio Petruzziello & Manuel Gesù Del Duca & Andrea Ariano & Ciro Aprea, 2022. "A Comprehensive Energy Model for an Optimal Design of a Hybrid Refrigerated Van," Energies, MDPI, vol. 15(13), pages 1-23, July.
    3. Meneghetti, Antonella & Dal Magro, Fabio & Romagnoli, Alessandro, 2021. "Renewable energy penetration in food delivery: Coupling photovoltaics with transport refrigerated units," Energy, Elsevier, vol. 232(C).
    4. Feiyue Qiu & Guodao Zhang & Ping-Kuo Chen & Cheng Wang & Yi Pan & Xin Sheng & Dewei Kong, 2020. "A Novel Multi-Objective Model for the Cold Chain Logistics Considering Multiple Effects," Sustainability, MDPI, vol. 12(19), pages 1-28, September.
    5. Yu Song & Xi Fang, 2023. "An Improved Strength Pareto Evolutionary Algorithm 2 with Adaptive Crossover Operator for Bi-Objective Distributed Unmanned Aerial Vehicle Delivery," Mathematics, MDPI, vol. 11(15), pages 1-25, July.
    6. Beatrice Marchi & Simone Zanoni, 2022. "Cold Chain Energy Analysis for Sustainable Food and Beverage Supply," Sustainability, MDPI, vol. 14(18), pages 1-16, September.
    7. Runfeng Yu & Lifen Yun & Chen Chen & Yuanjie Tang & Hongqiang Fan & Yi Qin, 2023. "Vehicle Routing Optimization for Vaccine Distribution Considering Reducing Energy Consumption," Sustainability, MDPI, vol. 15(2), pages 1-24, January.

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