Sustainable network design for a non-profit food bank supply chain with a heterogeneous fleet under uncertainty

Starvation and food insecurity are on an upward trajectory as the world population and food prices increase. Food insecurity continues to create life-threatening health concerns while a significant amount of food is wasted due to the ineffective management of food supply chains including inappropriate storage and transportation activities. To save surplus food, reduce food waste, and improve food security, this paper presents a multi-objective, multi-period, and multi-product mathematical model for a non-profit food bank supply chain considering cold chain transportation and storage facilities, heterogeneous fleet, and time limitations. In this research for the first time a three-objective two-stage stochastic program is developed in the non-profit food bank supply chain including 1) minimizing costs of food collection, storage, distribution or transportation, and food banks establishment, 2) minimizing carbon emissions of food waste and transportation as well as incrementing carbon emissions saving through preserving surplus food and 3) optimizing social performance including demand satisfaction, job creation, and unpleasant odor of food waste. Two solution approaches, namely NSGA-II and augmented e-constraint are employed and compared for small, medium, and large-scale problems. The parameters of the meta-heuristic algorithm are tuned using the Taguchi approach. Then the proposed model is utilized to tackle a real-life case study and the results indicate its efficiency. In addition, the results reveal that applying a heterogeneous fleet is necessary to reduce food waste and transportation costs where cold chain transportation and refrigerated fleets have significantly had direct and positive effects on demand satisfaction and food waste rate.

Automated summary

This paper presents a multi-objective, multi-period, and multi-product mathematical model for a non-profit food bank supply chain. The study found that using a heterogeneous fleet can reduce food waste and transportation costs, and have significant positive effects on demand satisfaction and food waste rate.