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.
Highlights
Improving the sustainability of a distribution network involves tradeoffs between multiple conflicting objectives, including minimizing transportation costs, fulfilling customer requirements, and limiting environmental impact
The research presented in this paper introduces a novel extension of the multi-objective vehicle routing problem for the sustainable distribution of perishable food products
The performance of the NGSA-II solution algorithm in solving the multi-objective sustainable vehicle routing problem (MO-SVRP) was tested on Solomon’s datasets [56], which are widely applied to measure the quality of solutions for a vehicle routing problem (VRP)
Summary
Improving the sustainability of a distribution network involves tradeoffs between multiple conflicting objectives, including minimizing transportation costs (e.g., fuel and vehicle maintenance costs, driver salaries), fulfilling customer requirements (e.g., on-time deliveries, short lead times), and limiting environmental impact (e.g., vehicle emissions). Optimizing sustainability in perishable food distribution is challenging, primarily because of temperature control requirements [1]. Temperature is a major determinant of the shelf life of a perishable product [2,3,4]. Even small or infrequent deviations from recommended temperature settings can significantly reduce product shelf life [5,6,7] because increased temperature accelerates the growth rate of the microorganisms that are responsible for quality degradation in perishable foods [5,8]. An estimated 8–23% loss in perishable food quality occurs during the distribution process [10]
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