Abstract
Modeling risk and uncertainty in designing reverse logistics problem
Highlights
Nowadays, designing reverse logistics plays an important role in gaining competitive advantages (Tonanont et al, 2008)
Comparisons of the results show that minimizing the costs had no direct relation with the kind of decision makers; in the most cases, risk-seeking decision maker gained more return products than risk-averse ones
The present paper focuses on designing and planning a reverse logistic network with the goal of maximizing return products to the chain and minimizing total cost, influenced by uncertainty rate of return, quality and quantity of returned products and risks related to demand, remanufacturing, recycling and disposal rate
Summary
Nowadays, designing reverse logistics plays an important role in gaining competitive advantages (Tonanont et al, 2008). There are different definitions for reverse logistics but According to Salema et al (2007) reverse logistics (RL) is defined as “The process of planning, implementing and controlling the efficient, effective inbound flow and storage of secondary goods and related information opposite to the traditional supply chain directions for the purpose of recovering value and proper disposal”. It is worth to mention that, unlike traditional supply chain, RL has an uncertainty inherent such as quality, price, time and amounts of return products (Soleimani & Govindan, 2014). These nature uncertainties imposes a high degree of complexity in RL design (Babazadeh et al, 2015).
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