A case-oriented approach to a lead/acid battery closed-loop supply chain network design under risk and uncertainty

Subulan, Kemal; Baykasoğlu, Adil; Özsoydan, Fehmi Burçin; Taşan, A. Serdar; Selim, Hasan

doi:10.1016/j.jmsy.2014.07.013

Cited by 77 publications

(41 citation statements)

References 36 publications

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“…They used a fuzzy programming approach for considering uncertainty. A scenario based stochastic and possibilistic mixed integer programming model for a multi-objective CLSC network design problem by considering financial and collection risks was proposed by Subulan et al [15]. The proposed hybrid model was applied to the lead/acid industry.…”

Section: Literature Reviewmentioning

confidence: 99%

Closed loop supply chain network design for the paper industry: A multi-objective stochastic robust approach

et al. 2017

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Closed loop supply chain design is to provide an optimal platform for efficient and effective supply chain management. It is an essential and strategic operation management problem in supply chain management, and usually includes multiple and conflicting objectives. A new mixed integer non-linear programming model for a multi-objective closed loop supply chain network design problem in the paper industry is developed under uncertainty. The objective functions are to minimize the total cost, maximize the total volume flexibility and minimize the total number of vehicles hired in order to fulfill the paper industry's policies towards a cleaner and green environment. Also, a novel hybrid solution is presented based on stochastic programming, robust optimization and fuzzy goal programming. A numerical example utilizing the real data from the paper industry in East Azerbaijan of Iran is designed and the model performance is assessed. Furthermore, a recently developed Dragonfly Algorithm (DA) employed to solve the given problem in large scales and compared with Genetic Algorithm (GA). The results indicated that the DA achieved better performance compared with the GA.

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Section: Literature Reviewmentioning

confidence: 99%

Closed loop supply chain network design for the paper industry: A multi-objective stochastic robust approach

et al. 2017

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“…With the development of economic globalization, the increasing vulnerability of supply networks (SN) has drawn substantial attention to risk management [1,2]. Any event that negatively affects the information and material flow between suppliers and demanders should be considered as a risk to the disruption [3].…”

Section: Introductionmentioning

confidence: 99%

Control and Backbone Identification for the Resilient Recovery of a Supply Network Utilizing Outer Synchronization

Geng

Xiao

2019

Applied Sciences

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The control and measurement for resilient recovery is important for a supply network facing disruption. Outer synchronization is useful for the supply network to recover to its scheduled state. In this paper, a dynamic model for a supply network is established, and measurement with memory of resilient recovery is proposed based on outer synchronization. An impulsive controller is designed to improve the control effectiveness. Afterwards, an algorithm is adopted to identify the resilient recovery backbone. Based on these factors, an efficient resilient recovery method considering cost is applied in the case study. This study improves the measurement and control of the supply network’s resilient recovery through outer synchronization, and is easily integrated with practical problems to make better control decisions.

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“…Moreover, a self-adaptive imperialist competitive meta-heuristic algorithm was proposed to solve the model. Subulan et al (2015) considered a lead/acid battery closed-loop supply chain network design under risk and uncertainty and proposed a scenario-based multi-objective stochastic and possibilistic mixed integer programming model to optimize it. Moghaddam (2015) developed a model for supplier selection and order allocation in a closed-loop supply chain network.…”

Section: Introductionmentioning

confidence: 99%

Designing a Multi-Product Multi-Period Supply Chain Network With Reverse Logistics and Multiple Objectives Under Uncertainty

Ghorabaee

Amiri

Olfat

et al. 2017

Technological and Economic Development of Economy

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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.

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A case-oriented approach to a lead/acid battery closed-loop supply chain network design under risk and uncertainty

Cited by 77 publications

References 36 publications

Closed loop supply chain network design for the paper industry: A multi-objective stochastic robust approach

Closed loop supply chain network design for the paper industry: A multi-objective stochastic robust approach

Control and Backbone Identification for the Resilient Recovery of a Supply Network Utilizing Outer Synchronization

Designing a Multi-Product Multi-Period Supply Chain Network With Reverse Logistics and Multiple Objectives Under Uncertainty

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