Designing a resilient multi-objective meat supply chain: a robust possibilistic approach

Population growth has led to more food demand, especially meat. Designing a meat supply chain is a complicated task, considering the uncertainty of food demand. In this paper, multi-objective mixedinteger linear programming is developed. The proposed model, contains four echelons, i.e., farms, abattoirs, retailers, and customers. The first objective function minimizes the total costs, the second objective function minimizes the distribution time and the third objective function minimizes the nonresiliencyof the network, simultaneously. To solve the suggested model an improved augmented ε- constraint is employed and as a result, a set of Pareto –optimal is given. To cope with uncertainty a Robust- possibilistic approach is obtained.

Keywords:

Meat supply chain , Multi-objective programming , Improved augmented ε- constraint , Robust possibilistic approach , resiliency , uncertainty