Designing a Food Security Supply Chain for Sustainable Oil Production Using a Non-Dominated Sorting Genetic Algorithm (NSGA-II) Approach

Abstract

Governments' key priorities include increasing food security and quality. Food security is influenced by food availability, financial ability to get food (affordability or accessibility), quality (utility), and sustainability. In light of food security concerns and the contractual approach, the current study presents and resolves a model for establishing supply chain networks for basic food products. The supply chain network investigated in this study includes two types of consumers, sunflower canola oil producer and oilseed suppliers. This study evaluated prior studies to identify food security dimensions and factors impacting a food security chain. Then, for field study, two questionnaires were constructed. The factors of food security and associated criteria were approved by research specialists who used the original questionnaire. The resulting questionnaire is then used to identify the most critical factors influencing food security in the supply chain being studied. The mathematical model of the supply chain that promotes domestic production and uses a contractual method was created. The "comprehensive criterion (LP-metric)" method was utilized to solve the problem in small dimensions. The multi-objective mathematics presented in this study is of the NP-hard type and the metaheuristic algorithm of Non- Dominated Sorting Genetic Algorithm (NSGA-II) was used to solve the model in large dimensions. In order to validate, the results of this algorithm were compared with the exact solution results (comprehensive benchmark method). The results of the studies indicate the appropriate performance of the metaheuristic algorithm. Finally, a sensitivity analysis was performed to examine the effect of parameters on the objective functions.