|
A novel attitude of robust optimization and risk management for network designing of closed-loop green supply chain
|
A. Taherinezhad   , A. Alinezhad , S. Gholami |
| Department of Industrial Engineering, Qazvin branch, Islamic Azad University, Qazvin, Iran |
|
|
Abstract: (458 Views) |
| A very important factor which needs to be considered in the process of designing an efficient supply chain is cost reduction. Meanwhile, to tackle climate change and to fight the increase in environmental pollution, the managers of organizations as well as scholars active in the field of designing supply chains, have started to adopt measures, which, on top of economic optimization, are also focused on environmental factors aimed at reducing pollutants in all sectors of the economy. Apart from the mentioned two variables, another factor influencing the supply chain is the delivery time. In the present paper, an integrated forward/reverse logistics network has been studied considering three objective functions including "minimizing environmental effects", "minimizing costs", and "minimizing delivery time", which are in fact the innovations of this research study. Model uncertainty has been dealt with through robustness of solutions. Scenario-based risk assessment methods have been applied to identifying and assessing potential risks. Then, taking into consideration the uncertain parameters, the robust scenario-based model of the problem has been submitted. Replacing the outputs of risk analysis (normalized risk priority number (RPN)) in the model for scenario occurrence, the authors have completed the model. Meanwhile, using the General Algebraic Modeling System (GAMS) software and the LP metric method, the model is transformed into a single-objective model and the problem is solved. The findings indicate that with the combination of risk assessment and robust optimization techniques, an efficient supply chain design will be realized, which is the study's another innovative aspect. |
|
| Keywords: Closed-loop Supply Chain (CLSC), Green Supply Chain, Robust Optimization, Risk Management |
|
|
Full-Text [PDF 599 kb]
(163 Downloads)
|
Type of Study: Research |
Subject:
General
Received: 2024/01/3 | Accepted: 2024/03/16 | Published: 2024/04/13
|
|
|
|
|
|
|
| Send email to the article author |
|
|
|
| Add your comments about this article |
|
|
|
