The optimization of resilience and sustainability using mathematical programming models and metaheuristic algorithms

The present study attempts to posit a suitable strategy for the optimal production with the maximum resilience and sustainability in the industrial dairy farms. The resilience and sustainability indicator was designed by integrating 5 indexes; they include the environmental, economic, social, technology and policy indexes and were modeled using the non-linear mathematical programming. The status of the industrial dairy farms in Khorasan Razavi province, Iran, was evaluated in terms of resilience and sustainability with the utilization of this indicator during 2016. The results of the initial estimation indicated the low level of resilience and sustainability of the probed dairy farms. Therefore, in order to clarify the application of the proposed model, all variables were considered as passive; hence, an intelligent and automatic model was postulated to optimize the resilience and sustainability in the industrial dairy farms. In order to gain the best outcome, the model was gauged by both the genetic algorithm and particle swarm optimization. Although both algorithms produced the same results, the validation tests unveiled the superiority of the genetic algorithm. Based on the results, the proposed model can improve the resilience and sustainability of production in the dairy farms and can reduce the environmental degradation brought about from the production process. For instance, the resilience and sustainability indicator increased up to 0.5% and profitability to 0.23%. Moreover, the greenhouse gas emissions and the energy intensity decreased to 0.09% and 0.02%, respectively. Our model can be adopted in variegated contexts to enhance the resilience and sustainability of the dairy farms and other production systems. (C) 2019 Published by Elsevier Ltd.