Designing an Integrated Engineering Model of Optimal Multi-Objective Green Supply Chain Planning for Banks with a Fuzzy Model and Solving the Model using Meta-Heuristic Algorithms

Abstract

Abstract The present research and model is aimed at presenting an integrated multi-objective optimal supply chain model of Sepah Bank's green supply chain in terms of model uncertainty using meta-heuristic algorithms and providing a suitable conceptual framework. In this regard, a multi-objective optimization model is presented and solved using fireworks algorithms based on Pareto Archive and NSGA-II. The green banking phenomenon has emerged with the same purpose in the banking system of the world and today it has made significant progress in theoretical and operational aspects. The interesting thing is that Islamic banking is not indifferent to this issue and it has a special focus on green banking under ethical banking.  Given the likelihood of larger environmental crises occurring in Iran, this responsibility for the Iranian banking system will be felt more tangibly. What is important is that the critical conditions of the future environmental trends in the country require that green banking be considered. In this paper, the Green Supply Chain of Sepah Bank is examined and modeled, which includes the three levels of Central Bank, Sepah Bank Branches and Investment Centers. The proposed model has three goals based on sustainability (economic, social and environmental). This model is solved using two fireworks algorithms and NSGA-II and the results of the two algorithms are compared based on quality, uniformity and diversity indices. Modeling results showed that the fireworks algorithm was more capable of exploring and extracting the solvable area than the NSGA-II algorithm. The NSGA-II algorithm also produces higher uniformity responses than the fireworks algorithm in less time.