Vol.:(0123456789) 1 3 Applied Intelligence https://doi.org/10.1007/s10489-021-02944-9 A closed-loop supply chain confguration considering environmental impacts: a self-adaptive NSGA-II algorithm Abdollah Babaeinesami 1  · Hamid Tohidi 1  · Peiman Ghasemi 2  · Fariba Goodarzian 3  · Erfan Babaee Tirkolaee 4 Accepted: 19 October 2021 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 Abstract Confguration of a supply chain network is a critical issue that contributes to choose the best combination for a set of facilities in order to attain an efective and efcient supply chain management (SCM). Designing a closed-loop distribution network of products is an important feld in supply chain network design, which ofers a potential factor for reducing costs and improving service quality. In this research, the question concerns a closed-loop supply chain (CLSC) network design considering suppliers, assembly centers, retailers, customers, collection centers, refurbishing centers, disassembly centers and disposal centers. It aims to design a distribution network based on customers’ needs in order to simultaneously minimize the total cost and total CO 2 emission. To tackle the complexity of the problem, a self-adaptive non-dominated sorting genetic algorithm II (NSGA-II) algorithm is designed, which is then evaluated against the ε-constraint method. Furthermore, the performance of the algorithm is then enhanced using the Taguchi design method to tune its parameters. The results indicate that the solution time of the self-adaptive NSGA-II approach performs better than the epsilon constraint method. In terms of the self-adaptive NSGA-II algorithm, the average number of Pareto solutions (NPS) for small and medium-sized problems is 6.2 and 11, respectively. The average mean ideal distance (MID) for small and medium-sized problems is 2.54 and 5.01, respectively. Finally, the average maximum spread (MS) for small and medium-sized problems is 3100.19 and 3692.446, respectively. The fndings demonstrate that the proposed self-adaptive NSGA-II is capable of generating efcient Pareto solutions. Moreover, according to the results obtained from sensitivity analysis, it is revealed that with increasing the capac- ity of distribution centers, the amount of shortage of products decreases. Moreover, as the demand increases, the number of established retailers rises. The number of retailers is increasing to some extent to establish 7 retailers. Keywords Closed-loop supply chain network · Environmental impacts · Mathematical modeling · Self-adaptive NSGA-II algorithm 1 Introduction A supply chain consists of all facilities, equipment, duties, tasks, and activities which are involved in delivering some goods or services, from suppliers (as the origin points) to customers. It includes planning and managing supply and demand, production and programmed delivery date, storing, inventory control, distribution, and delivering the service to the customer [6, 44]. Supply chain management (SCM) coordinates all these activities in a way that customers can obtain high-quality and insured services at the lowest price possible [42]. In other words, SCM can itself create a * Erfan Babaee Tirkolaee erfan.babaee@istinye.edu.tr Abdollah Babaeinesami st_a_babaeinesami@azad.ac.ir Hamid Tohidi h_tohidi@azad.ac.ir Peiman Ghasemi peiman.ghasemi@gutech.edu.om Fariba Goodarzian Fariba.Goodarzian@mirlabs.org 1 Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran 2 Department of Logistics, Tourism and Service Management, German University of Technology in Oman (GUtech), Muscat, Oman 3 Machine Intelligence Research Labs (MIR Labs), Scientifc Network for Innovation and Research Excellence, Washington, USA 4 Department of Industrial Engineering, Istinye University, Istanbul, Turkey