Integrated Forward-reverse Logistics Network Design under Uncertainty and Reliability Consideration

Abstract

Abstract. This paper proposes a robust optimization model for robust and reliable design of an integrated forward-reverse logistics network with hybrid facilities under uncertainty and random facility disruptions. The proposed model utilizes several e ective reliability strategies to mitigate the impact of random facility disruptions. First, the proposed model allows two types of hybrid facilities, namely, reliable and unreliable, to be located in the concerned logistics network where unreliable ones may be partially or fully disrupted, and thus a percentage of their capacities may be lost. However, they can still serve their customers with the remaining of their available capacities. Furthermore, a sharing strategy is taken into account, in which goods can be shipped from reliable hybrid facilities to unreliable ones to compensate their lost capacity. A robust optimization approach is applied on the developed model to handle the uncertainties in the parameters of the concerned network. Finally, several numerical experiments along with a sensitivity analysis are conducted to illustrate the signi cance and applicability of the proposed model as well as the e ectiveness of the robust optimization approach in this context.

Designing a multi-objective closed-loop supply chain: a two-stage stochastic programming, method applied to the garment industry in Montréal, Canada

“…El-sayed et al ( 2010 ) developed a network with repair, remanufacture, and recycle facilities in the forward and backward supply chain. Hatefi et al ( 2016 ) just studied refurbishing in their network. Reddy et al ( 2019 ) focused on remanufacturing in multi-period and single products conditions.…”

“…Moreover, forward and backward directions have been studied in the literature. Among them is the work of Hatefi et al ( 2016 ), where he solved the problem with the exact approach. Also, Porkar et al ( 2018 ) designed the problem in multi-period and multi-products conditions and solved a numerical example with a meta-heuristic algorithm.…”

Ensuring sustainability in the reverse supply chain in case of the ripple effect: A two-stage stochastic optimization model

“… Afshari et al, 2016 ; Aydin, 2020 ; Ayvaz et al, 2015 ; Bertsimas and Sim, 2004 ; Chakraborty et al, 2018 ; De Rosa et al, 2013 ; Demirel et al, 2016 ; Doan et al, 2018 ; Fang et al, 2011 ; Feitó-Cespón et al, 2017 ; Ghadge et al, 2016 ; Gu and Gao, 2012 ; Hamdan and Diabat, 2020 ; Hamidieh et al, 2017 ; Hatefi and Jolai, 2014 ; Hatefi et al, 2015 ; Hatefi et al, 2016 ; Heydari and Ghasemi, 2018 ; Heydari et al, 2018 ; Hosseini-Motlagh et al, 2019 ; Hosseini-Motlagh et al, 2020 ; Hosseini and Sarder, 2019 ; Hosseini and Ivanov, 2019 ; Hosseini et al, 2019a ; Hosseini et al, 2019b ; Ivanov et al, 2014a ; Ivanov et al, 2014b ; Ivanov et al, 2016 ; Ivanov et al, 2017 ; Jabbarzadeh et al, 2014 ; Jain et al, 2017 ; John et al, 2018 ; Kinra et al, 2019 ; Liao, 2018 ; Mohapatra et al, 2019 ; Niknejad and Petrovic, 2014 ; Pavlov et al, 2019 ; Pishvaee et al, 2011 ; Phuc et al, 2017 ; Qiaolun and Tiegang, 2012 ; Qiaolun and Tiegang, 2013 ; Ren et al, 2020 ; Sawik, 2017 ; Setak et al, 2019 ; Shuang et al, 2019 ; Suryawanshi and Dutta, 2019 ; Tosarkani and Amin, 2019 ; Tucker et al, 2020 ; Yu and Solvang, 2017 ; Zhang et al, 2018 ; Zhao et al, 2018 .…”

A Bi-Objective Programming Model for Reliable Supply Chain Network Design under Facility Disruption

“…Hatefi and Jolai [26][27] and Torabi et al [28], for instance, devised disruption scenarios so as to overcome complete and partial disruptions going on in facilities in a supply chain network. Moreover, in order to model random facility disruptions to solve a forward-reverse supply chain network design problem, Hatefi et al [29][30][31] developed several disruption strategies. In the same way, Azad et al [32] expanded reliability scenarios to control the existing disruptions happening in facilities and transportation paths.…”