Supply chain network design using trade credit and bank credit: A robust optimization model with real world application

Alavi, Seyyed Hossein; Jabbarzadeh, Armin

doi:10.1016/j.cie.2018.08.005

Cited by 40 publications

(11 citation statements)

References 93 publications

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“…Consequently, to reduce the computational time of solving the problem, a heuristic algorithm based on the Lagrangian relaxation approach has been developed. Lagrangian relaxation method is a practical approach to solve complicated mathematical programming models and used in the field of supply chain management in many pieces of research (Heidari-Fathian and Pasandideh, 2018; Alavi and Jabbarzadeh, 2018; Kheirabadi et al , 2019; Yousefi-Babadi et al , 2017; Cui et al , 2016; Ahmadi-Javid and Hoseinpour, 2015; Lashine et al , 2006). This method simplifies the mathematical model by relaxing and inserting complex constraints to the objective function of the model as penalty functions.…”

Section: Solution Method: Lagrangian Relaxation Algorithmmentioning

confidence: 99%

A reliable location-inventory-routing three-echelon supply chain network under disruption risks

Mohebban-Azad

Abtahi

Zenouz

2021

JM2

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Purpose This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption risks and uncertainty in the inventory system. Design/methodology/approach A robust optimization approach is used to deal with the effects of uncertainty, and a mixed-integer nonlinear programming multi-objective model is proposed. The first objective function seeks to minimize inventory costs, such as ordering costs, holding costs and carrying costs. It also helps to choose one of the two modes of bearing the expenses of shortage or using the excess capacity to produce at the expense of each. The second objective function seeks to minimize the risk of disruption in distribution centers and suppliers, thereby increasing supply chain reliability. As the proposed model is an non-deterministic polynomial-time-hard model, the Lagrangian relaxation algorithm is used to solve it. Findings The proposed model is applied to a real supply chain in the aftermarket automotive service industry. The results of the model and the current status of the company under study are compared, and suggestions are made to improve the supply chain performance. Using the proposed model, companies are expected to manage the risk of supply chain disruptions and pay the lowest possible costs in the event of a shortage. They can also use reverse logistics to minimize environmental damage and use recycled goods. Originality/value In this paper, the problem definition is based on a real case; it is about the deficiencies in the after-sale services in the automobile industry. It considers the disruption risk at the first level of the supply chain, selects the supplier considering the parameters of price and disruption risk and examines surplus capacity over distributors’ nominal capacity.

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Section: Solution Method: Lagrangian Relaxation Algorithmmentioning

confidence: 99%

A reliable location-inventory-routing three-echelon supply chain network under disruption risks

Mohebban-Azad

Abtahi

Zenouz

2021

JM2

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“…Alavi and Jabbarzadeh ( 2018 ) applied an RO approach for a CLSCN design to deal with the uncertainty of recycled products and market demand. Kim et al ( 2018 ) utilized an RO method for a fashion CLSCN planning under uncertainty of market demand and RL flow.…”

Section: Literature Reviewmentioning

confidence: 99%

Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

Alizadeh-Meghrazi

Tosarkani

Amin

et al. 2022

Environ Dev Sustain

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Wearing a mask or a face covering became mandatory in indoor public spaces to reduce the spread of coronavirus disease 2019 (COVID-19). The Ontario government (i.e., a province of Canada) encouraged medical supply producers to switch their operations to produce personal protective equipment (e.g., masks) during the COVID-19 pandemic. In this regard, there are several uncertain parameters (e.g., operational costs, market demand, and capacity levels of facilities) affecting the performance of producers in a medical supplies market. In this study, we propose a flexible optimization model to configure a robust mask supply chain network under uncertainty. Furthermore, companies are supposed to undertake their operations based on sustainable manners, in compliance with provincial policy, in Ontario. Therefore, the proposed flexible optimization model is extended to a robust multi-objective model to investigate sustainable strategies in a mask supply chain network design problem. The applicability of this model is demonstrated for the Greater Toronto Area, Canada.

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“…Several studies examined the impact of bankruptcy cost on the supply chain's operational decisions under the bank credit contract (e.g. [1], [26] and [42]). Recently, some literatures investigated the financially weaker partner's bank financing model which incorporates a stronger partner's intermediary and guarantee, and analyzed the impact of risk sharing or warranty mechanism on the bank financing strategy (such as, [9], [21] and [41]).…”

Section: Supply Chain Financementioning

confidence: 99%

A financing model with rebate contract in a capital-constrained supply chain

Zhan

2021

RAIRO-Oper. Res.

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In a two-level supply chain that includes one supplier and one capital-constrained retailer, this paper investigates a new bank financing model (Model N), in which, the supplier requires the retailer to order a quantity that is not less than a specified minimum ordering quantity (MOQ), rebates the per unit excess that sells over the MOQ, and promises to provide a partial warranty for the bank credit risk if the revenue is below the bankruptcy level of the retailer with the MOQ. This study shows that retailer's optimal order quantity increases with MOQ level and decreases with rebate rate, while supplier's optimal wholesale price shows an opposite tendency. Compared to the traditional bank financing model (Model T), the model N with an appropriate rebate contract will result in a larger order quantity of retailer. Furthermore, model N would benefit the entire supply chain and a Pareto zone of MOQ (or rebate rate) exists, in which, model N outperforms model T for each player. The numerical experiments are performed to illustrate that with increasing the marginal production cost of supplier, the MOQ level is decreasing while rebate rate is increasing in the Pareto zone.

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Supply chain network design using trade credit and bank credit: A robust optimization model with real world application

Cited by 40 publications

References 93 publications

A reliable location-inventory-routing three-echelon supply chain network under disruption risks

A reliable location-inventory-routing three-echelon supply chain network under disruption risks

Design and optimization of a sustainable and resilient mask supply chain during the COVID-19 pandemic: A multi-objective approach

A financing model with rebate contract in a capital-constrained supply chain

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