Abstract
Nowadays, there is a great deal of interest in developing supply chain networks with the goal of optimisation. This paper addresses a new stochastic optimisation model by using a two-stage stochastic programming for a closed-loop supply chain network design problem. To control the uncertainty circumstances of manufacturing of products, customers’ demand, prices of products and its returned rates, the financial risk is considered as a distinguished objective function to find a robust solution. To address the developed model, a new recent nature-inspired algorithm, namely, Whale Optimisation Algorithm (WOA) and also Particle Swarm Optimisation (PSO) as a popular method in swarm intelligence algorithms are utilised in this study. In addition to this development, Genetic Algorithm (GA) and Simulated Annealing (SA) as the well-known metaheuristics used repeatedly among the literature are employed to have a comprehensive comparison. In order to be faired, a popular method for calibration called Response Surface Method (RSM) is applied to tune the algorithms’ parameters. Finally, some evaluation metrics to assess the Pareto optimal fronts of algorithms’ quality are considered to conduct a comparative study using statistical analyses and some sensitivity analyses are performed through an industrial example.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
Anita Abdi
Anita Abdi was born and raised in Sari, Iran. She has earned her M. Sc. in Industrial Engineering from Mazandaran University of Science and Technology, Babol Iran. She earned her B.Sc. from University of Science and Technology of Mazandaran, Behshahr, Iran. Her researchers are mainly about supply chain management and optimization techniques (email: [email protected]).
Andisheh Abdi
Andisheh Abdi was born and raised in Sari, Iran. She graduated in her M. Sc. of Industrial Engineering from Islamic Azad University – Tehran North Branch. She earned her B.Sc. from Iran University of Science and Technology, Behshahr, Iran. She worked for two years at the Production Planning and Control unit in an automotive company. Currently, she works in planning unit at the food production and distribution company. Her researchers are about supply chain management and also marketing issues (email: [email protected]).
Amir Mohammad Fathollahi-Fard
Amir Mohammad Fathollahi-Fard was born and raised in Sari, Iran. He received his degrees of B.Sc. (2016) and M.Sc. (2018) in Industrial Engineering from University of Science & Technology of Mazandaran, Behshahr, Iran. He is currently a Ph. D. Candidate in Industrial Engineering from Amirkabir University of Technology, Tehran, Iran. His main researches are about solving combinatorial optimization problems by using novel heuristics and metaheuristics. He is interested in developing novel mathematical models in the area of Healthcare Management, Supply Chain Management, Green Logistics and Sustainable Operations Management. He has published more than 50 scientific papers in high-ranked journals such as ASOC, JCLP, EAAI, CAIE and NCAA etc. (email: [email protected]).
Mostafa Hajiaghaei-Keshteli
Mostafa Hajiaghaei-Keshteli was born and raised in Babol, Iran. He earned his B.Sc. from Iran University of Science & Technology, Tehran, Iran (2004); M.Sc. from University of Science & Culture, Tehran, Iran (2006); and Ph.D. from Amirkabir University of Technology (Tehran-Polytechnic), Tehran, Iran (2012); all in Industrial Engineering. He currently an associate professor in Industrial Engineering at University of Science & Technology of Mazandaran, Behshar, Iran. He has over 10 years of experience in Business Development, System Analysis, Inventory and Project Management. Mostafa also has worked for many corporations in Iran and has held the positions of consulter, planning and project manager and VP. The main focus of his research is in the area of Inventory Control, Supply Chain Network, Transportation and Meta-heuristics. He has published more than 100 scientific papers in high-ranked journals such as ESWA, CAIE, KNOSYS, JCLP, NCAA, IEEE and ASOC etc. (email: [email protected]).