A Resilient Green Meat Supply Chain Network Design; Applying Multi-Objective Robust Optimization Approach

In this paper, the resilience green meat supply chain network is investigated by proposing a multi-product, multi-period, multi-echelon and multi-objective mixed-integer linear programming formulation considering three conflicting objectives: minimizing total transportation and location costs, minimizing total CO2 emissions released from transportation, and maximizing total capacity utilization. Disruption in each echelon of the green meat supply chain is considered. Also, transportation cost and demandparameters are sources of uncertainty, therefore, in order to cope with the uncertainties, robust optimization approach is applied. A solution approach based on the multi-choice goal programming (MCGP) approach considering utility function is utilized to solve the proposed model. As a result, the optimal product flow and number of each echelon will be determined. Finally, a set of numerical experiments and sensitivity analyses on uncertainty level and demand parameters to investigate the efficiency of the proposed model are conducted.

Keywords:

Meat supply chain , Multi-objective programming , Mixed-integer linear programming , Ben-Tal robust optimization , Multi-choice goal programming