  How to ensure accessibility to food and nutrition while food supply chains
suffer from demand and supply uncertainties caused by disruptive forces such as
the COVID-19 pandemic and natural disasters is an emerging and critical issue.
Unstable access to food influences the level of nutrition that weakens the
health and well-being of citizens. Therefore, a food accessibility evaluation
index is proposed in this work to quantify how well nutrition needs are met.
The proposed index is then embedded in a stochastic multi-objective
mixed-integer optimization problem to determine the optimal supply chain design
to maximize food accessibility and minimize cost. Considering uncertainty in
demand and supply, the multi-objective problem is solved in a two-phase
simulation-optimization framework in which Green Field Analysis is applied to
determine the long-term, tactical decisions such as supply chain configuration,
and then Monte Carlo simulation is performed iteratively to determine the
short-term supply chain operations by solving a stochastic programming problem.
A case study is conducted on the beef supply chain in Qatar. Pareto efficient
solutions are validated in discrete event simulation to evaluate the
performance of the designed supply chain in various realistic scenarios and
provide recommendations for different decision-makers.
