Collaborative Decision-Making Model of Green Supply Chain: Cloud-Based Metaheuristics

The inter-organizational collaborative supply chain (SC) network involves the collaboration of various firms and decision-makers to increase the whole efficiency of an SC network. There is often a conflict between operations and environmental managers in how to design a supply network to simultaneously reduce greenhouse gas emissions and logistics costs. In this paper, a twodimensional collaborative decision-making (CDM) model for a SC network is developed. The proposed network is assumed to deliver the final product to customers in the forward flow from suppliers through manufacturers and distribution centers (DCs). Simultaneously, collecting recycled products from customers and entering them into a recovery cycle is examined. Mathematical modeling of this problem is going to minimize both the total costs and the environmental negative effects. To effectively manage the conflict, Pareto solutions for the bi-objective model are provided. Moreover, a cloud-based simulated annealing algorithm (CSA) has been applied for the first time in this area. We have compared its performance with the genetic algorithm (GA) and the simulated annealing (SA) algorithm of the literature.