Simulation-based multi-objective model for supply chains with disruptions in transportation

Unpredictable disruptions (e.g., accidents, traffic conditions, among others) in supply chains (SCs) motivate the development of decision tools that allow designing resilient routing strategies. The transportation problem, for which a model is proposed in this paper, consists of minimizing the stochastic transportation time and the deterministic freight rate. This paper extends a stochastic multi-objective minimum cost flow (SMMCF) model by proposing a novel simulation-based multi-objective optimization (SimMOpt) solution procedure. A real case study, consisting of the road transportation of perishable agricultural products from Mexico to the United States, is presented and solved using the proposed SMMCF-Continuous/SimMOpt solution framework. In this case study, time variability is caused by the inspection of products at the U.S.-Mexico border ports of entry. The results demonstrate that this framework is effective and overcomes the limitations of the multi-objective stochastic minimum cost flow problem (which becomes intractable for large-scale instances).