Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Multi-Objective Model for Sustainable Perishable Food Distribution Considering the Impact of Temperature on Vehicle Emissions and Product Shelf Life

Version 1 : Received: 4 August 2020 / Approved: 5 August 2020 / Online: 5 August 2020 (04:34:06 CEST)

A peer-reviewed article of this Preprint also exists.

Gharehyakheh, A.; Krejci, C.C.; Cantu, J.; Rogers, K.J. A Multi-Objective Model for Sustainable Perishable Food Distribution Considering the Impact of Temperature on Vehicle Emissions and Product Shelf Life. Sustainability 2020, 12, 6668. Gharehyakheh, A.; Krejci, C.C.; Cantu, J.; Rogers, K.J. A Multi-Objective Model for Sustainable Perishable Food Distribution Considering the Impact of Temperature on Vehicle Emissions and Product Shelf Life. Sustainability 2020, 12, 6668.

Abstract

The food distribution process is responsible for significant quality loss in perishable products. However, preserving quality is costly and consumes a tremendous amount of energy. To tackle the challenge of minimizing transportation costs and CO2 emissions while also maximizing product freshness, a novel multi-objective model is proposed. The model integrates a vehicle routing problem with temperature, shelf life, and energy consumption prediction models, thereby enhancing its accuracy. Non-dominated sorting genetic algorithm II is adapted to solve the proposed model for the set of Solomon test data. The conflicting nature of these objectives and the sensitivity of the model to shelf life and shipping container temperature settings are analyzed. The results show that optimizing freshness objective degrade the cost and the emission objectives, and the distribution of perishable foods are sensible to the shelf life of the perishable foods and temperature settings inside the container.

Keywords

sustainable distribution; food perishability; multi-objective optimization; temperature prediction; shelf life; food waste; NSGA-II

Subject

Engineering, Industrial and Manufacturing Engineering

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