An integrated Multi-Objective Optimization Model for Bank Green Supply Chain Network Under Uncertainty Using Fireworks and NSGA-II Algorithm

Abstract

The research and the proposed model have been performed with the aim of providing integrated multi-objective planning of Bank Sepah green supply chain, in uncertainty and model solution, using meta-heuristic algorithm and providing a suitable conceptual framework. In this regard, first, a model is presented for Multi-Objective Optimization of modm, and then, it is solved using the fireworks algorithm fireworks based on the Pareto archive and NSGA-II genetics. The Green Banking phenomenon has been developed with the same purpose, in the world's banking systems and nowadays has made significant progress in theoretical and operational terms. Interestingly, Islamic banking is not indifferent to this issue and pays special attention to green banking under the coverage of Ethical banking. The important issue is that in the critical situation of the future trend of the environment in Iran, green banking requires the attention of decision-makers. In this dissertation, Sepah Bank's green supply chain has been reviewed and modeled, which includes three levels of the Central Bank, Sepah Bank branches, and investment centers. The proposed model, based on sustainability dimensions, has three goals. This model is solved using two fireworks and NSGA-II algorithms, and the results of the two algorithms are compared based on quality, evenness, and dispersion indices. The results of the model solution demonstrated that the fireworks algorithm has a greater ability to explore and extract the feasible region of the response than the NSGA-II algorithm. Moreover, the NSGA-II algorithm, compared to the fireworks algorithm, produces higher uniformity responses in less time.