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Seifbarghy, M., Karbalaei Esmaeili, M. (2021). A Mathematical Location-Inventory Model for Designing a Forward /Backward Logistic Network under Demand and Return Uncertainty with Multiple Capacity Levels. Electronic and Cyber Defense, 23(72), 23-39.
Mehdi Seifbarghy; Mehdi Karbalaei Esmaeili. "A Mathematical Location-Inventory Model for Designing a Forward /Backward Logistic Network under Demand and Return Uncertainty with Multiple Capacity Levels". Electronic and Cyber Defense, 23, 72, 2021, 23-39.
Seifbarghy, M., Karbalaei Esmaeili, M. (2021). 'A Mathematical Location-Inventory Model for Designing a Forward /Backward Logistic Network under Demand and Return Uncertainty with Multiple Capacity Levels', Electronic and Cyber Defense, 23(72), pp. 23-39.
Seifbarghy, M., Karbalaei Esmaeili, M. A Mathematical Location-Inventory Model for Designing a Forward /Backward Logistic Network under Demand and Return Uncertainty with Multiple Capacity Levels. Electronic and Cyber Defense, 2021; 23(72): 23-39.

A Mathematical Location-Inventory Model for Designing a Forward /Backward Logistic Network under Demand and Return Uncertainty with Multiple Capacity Levels

مدیریت زنجیره تأمین
Article 3, Volume 23, Issue 72, February 2022, Pages 23-39    PDF (507.88 K)
Document Type: Research/ Original/ Regular Article
Authors
Mehdi Seifbarghy* 1; Mehdi Karbalaei Esmaeili2
1Department of Industrial Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran
22Department of Industrial Engineering, Faculty of Mechanical and Industrial Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran
Receive Date: 16 August 2021,  Revise Date: 27 January 2022,  Accept Date: 29 January 2022 
Abstract
Today, the competitive business environment has led to increasing cooperation among companies as the members of supply chain networks. In this area, the supply chain logistics network design is an important subject due to its effect on the responsiveness and efficiency. Over the past few years, due to environmental issues, their legal requirements and economic benefits, great attention has been paid to inverse logistics. In this paper, a mixed integer stochastic location-inventory model has been proposed for the integrated design of the network of a multi-period multi-product closed loop supply chain considering multiple capacity levels for facilities. The market demand and correspondingly the return value are considered to be uncertain in order to make the model close to the real-life conditions. Since the capacitated facility location problem considered in this research is an NP-hard type problem, we have used two meta-heuristic algorithms including the genetic algorithm (GA) and the Bees algorithms (BA) for solving this problem. Some numerical problems are designed and solved to assess the performance of the model and solution heuristics. From the viewpoint of solution quality, the BA outperforms the GA (by an average of 11.6%) whilst from the viewpoint of solution time, the GA is five times faster than the BA on average.
Keywords
Closed Loop Supply Chain; Network Design; Uncertainty; Genetic Algorithm; Bees Algorithm
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