Designing a multi-product multi-period supply chain network with reverse logistics and multiple objectives under uncertainty

Abstract

Integration of reverse logistics processes into supply chain network design can help to achieve a network that incorporates environmental factors as well as economic factors. In this study, a new integrated approach is proposed to address designing a multi-product, multi-period supply chain network with reverse logistics. The framework of the proposed approach includes green supplier evaluation and a mathematical model in an uncertain environment. To the best of our knowledge, integration of green supplier evaluation into the designing supply chain network with reverse logistics has not been considered in the literature. This integration can help to incorporate experts’ opinions about environmental impact of suppliers in the network design. Minimization of total cost and maximization of total greenness score of purchased raw materials/components are two objectives of the model. The fuzzy EDAS method is used to determine the greenness scores of suppliers. Also, demand of customers and capacity of suppliers are defined using fuzzy numbers and a fuzzy method is used to obtain trade-off solutions. The proposed approach is applied to designing the supply chain network of a home appliance company. The results show that the proposed approach is feasible and efficient to obtain solutions to design the supply chain network.

Keywords:

• supply chain network design
• reverse logistics
• multi-objective decision-making (MODM)
• fuzzy EDAS
• fuzzy MODM
• closed-loop supply chain

JEL Classification:

• C44
• C61
• D80
• L60
• Q21
• Q50

Additional information

Notes on contributors

Mehdi Keshavarz Ghorabaee

Mehdi KESHAVARZ GHORABAEE received the B.S. degree in electrical engineering from University of Guilan, Rasht, Iran in 2010 and the M.S. degree in production management from Allameh Tabataba’i University, Tehran, Iran in 2013. He is currently working toward the PhD degree in Operations Research at Allameh Tabataba’i University. He has published some papers in leading international journals such as Robotics and Computer-Integrated Manufacturing, The International Journal of Advanced Manufacturing Technology, Journal of Cleaner Production and Applied Mathematical Modelling. His research interests include multi-criteria decision making (MCDM), multi-objective evolutionary algorithms, genetic algorithm, fuzzy MCDM, inventory control, supply chain management, scheduling and reliability engineering.

Maghsoud Amiri

Maghsoud AMIRI is Professor at the Department of Industrial Management of Allameh Tabataba’i University, Tehran, Iran. He received PhD degree in industrial engineering from Sharif University of Technology, Tehran, Iran. He has published many papers in leading international journals. His research interests include multi-criteria decision-making (MCDM), data envelopment analysis (DEA), design of experiments (DOE), response surface methodology (RSM), fuzzy MCDM, inventory control, supply chain management, simulation and reliability engineering.

Laya Olfat

Laya OLFAT is an Associate Professor with the Department of Industrial Management of Allameh Tabataba’i University, Tehran, Iran. She received the M.S. degree in industrial engineering from the University of Birmingham, UK and the PhD degree in management (Operations Research) from the University of Tehran, Iran. She is currently Dean of the Management and Accounting Faculty of Allame Tabataba’i University. Her research interests include supply chain management (SCM), production planning, inventory control, scheduling, green SCM, optimization, multi-criteria decision making, project management and manufacturing systems.

S. M. Ali Khatami Firouzabadi

S. M. Ali KHATAMI FIROUZABADI is an Associate Professor with the Department of Industrial Management of Allameh Tabataba’i University, Tehran, Iran. He received his PhD degree in industrial engineering from University of Leeds, UK in 2005. His main research interests are operations research, mathematical programming, production planning, inventory control, multi-criteria decision-making (MCDM) and fuzzy MCDM.