Resilient supplier selection and order allocation under operational and disruption risks

Torabi, S. Ali; Baghersad, Milad; Mansouri, S. Afshin

doi:10.1016/j.tre.2015.03.005

Cited by 347 publications

(201 citation statements)

References 39 publications

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“…Identifying flexibility and resilience within the supply chain is critical for reducing potential risks [4]. Lee [27] proposed the triple "A" principle of "Alignment, Adaptability and Agility" as strategies for supply chain resilience.…”

Section: Resilient Supply Chains and Supplier Selection Problemsmentioning

confidence: 99%

“…Kristianto et al [31] designed a two-stage programming with fuzzy shortest path model of resilient supply chain network. Torabi et al [4] proposed a bi-objective mixed possibilistic, two-stage stochastic programming model to address supplier selection and order allocation problem to build the resilient supply base under operational and disruption risks.…”

Section: Resilient Supply Chains and Supplier Selection Problemsmentioning

confidence: 99%

“…Mitra et al, Sawik, and Torabi et al [4,34,35] separately pointed out several critical factors in designing a resilient supply chain and selecting resilient suppliers. Peck [36] found that high levels of collaboration with suppliers and flexibility in the enterprise itself can improve resilience.…”

Section: Resilient Supply Chains and Supplier Selection Problemsmentioning

confidence: 99%

“…After reviewing the literature, quality, cost, and delivery are considered to be the dominant criteria in most supplier selection systems [4,35]. In addition, a supplier needs to be able to organize the level of management, ability of risk reduction, and responsiveness.…”

Section: Supplier Selection Criteriamentioning

confidence: 99%

See 3 more Smart Citations

Integrated Supplier Selection Framework in a Resilient Construction Supply Chain: An Approach via Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA)

et al. 2017

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Construction supply chain management is a unique and problematic issue within the construction industry due to its inevitable external risks and variations. The resilience capability of a supplier is of significance in supplier selection; a supplier selected in the context of a resilient construction supply chain (RCSC) is referred to in this research as a "resilient construction supplier". This paper proposes a supplier selection framework tailored to effective information integration for supply chain management. The proposed framework works by integrating building information modeling (BIM) and a geographic information system (GIS) in a RCSC. BIM and GIS together provide highly transparent construction material information, enhanced supply chain status visualization, and workable access information for supplier selection. Supplier performance is evaluated via seventeen resilient criteria under a combined methodology consisting of the analytic hierarchy process (AHP) and grey relational analysis (GRA); AHP and GRA weigh the criteria and rank the suppliers respectively. By varying the weightings given to each criterion, sensitivity analysis was conducted to identify the criteria of resilience which impact the selection priorities of suppliers. An illustrative example is also provided to show the overall process of the proposed framework.

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Section: Resilient Supply Chains and Supplier Selection Problemsmentioning

confidence: 99%

Section: Resilient Supply Chains and Supplier Selection Problemsmentioning

confidence: 99%

Section: Resilient Supply Chains and Supplier Selection Problemsmentioning

confidence: 99%

Section: Supplier Selection Criteriamentioning

confidence: 99%

See 2 more Smart Citations

Integrated Supplier Selection Framework in a Resilient Construction Supply Chain: An Approach via Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA)

et al. 2017

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“…The planning horizon is assumed to cover a set of period t∈ (0, 1, 2… T). Along this horizon disruption may occur and reconfiguration decisions are made only in the planning periods td t ∈ T. This disruption reconfiguration planning periods are assumed to be three periods following the works of Hendricks & Singhal, (2005), Losada et al, (2010Losada et al, ( , 2012, Sahebjamnia et al, (2015) and Torabi et al, (2015). The first period within reconfiguration planning horizon when disruption occurs is termed as 'onset period' and the remaining two periods are termed as 'recovery periods' as shown in figure 1.As our problem is long term strategic in nature where each period may represent one or more years, inventory decisions do not provide representative information and are not considered in the model i.e.…”

Section: Problem Description and Model Formulationmentioning

confidence: 99%

Multi Objective Supply Chain Network Reconfiguration Under Disruptions

Rajagopal¹,

Venkatesan²,

Agrawal³

2017

World Conference on Supply Chain Management

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Disruption in today's complex and global supply chain network (SCN) results in a negative impact on business performance. Companies try to manage disruptions by shifting the production/sourcing to undisrupted facilities, expanding the capacity at selected facilities, re-routing transportation and outsourcing the unmet demands. Models and methods to find a cost effective SCN reconfiguration to deal with disruption need attention. In this work, a SCN reconfiguration in a dynamic planning horizon under facility disruption is modelled mathematically with the objectives of minimizing the expected total cost and delivery time. The augmented ε-constraint method is proposed as a solution approach to obtain a set of Pareto optimal solutions. Numerical illustration with disruption scenarios is presented and our results show that facility with minimum distance to most customers serve majority of total customer demand. During disruption onset period, unmet demands are shifted to least utilised facility. During recovery periods, the facility with minimum distance to most customers is expanded to satisfy unmet demands. More capacity expansion occurred in minimum cost solution than in minimum time solution as more number of facilities are opened in latter than in former. The capacity utilization of facilities in minimum cost solutions are higher compared to that of minimum time solution.

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A mathematical modeling approach for supply chain management under disruption and operational uncertainty

Badejo

Ierapetritou

2023

AIChE Journal

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In this work, we proposed a two-stage stochastic programming model for a fourechelon supply chain problem considering possible disruptions at the nodes (supplier and facilities) as well as the connecting transportation modes and operational uncertainties in form of uncertain demands. The first stage decisions are supplier choice, capacity levels for manufacturing sites and warehouses, inventory levels, transportation modes selection, and shipment decisions for the certain periods, and the second stage anticipates the cost of meeting future demands subject to the first stage decision. Comparing the solution obtained for the two-stage stochastic model with a multi-period deterministic model shows that the stochastic model makes a better first stage decision to hedge against the future demand. This study demonstrates the managerial viability of the proposed model in decision making for supply chain network in which both disruption and operational uncertainties are accounted for.

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Resilient supplier selection and order allocation under operational and disruption risks

Cited by 347 publications

References 39 publications

Integrated Supplier Selection Framework in a Resilient Construction Supply Chain: An Approach via Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA)

Integrated Supplier Selection Framework in a Resilient Construction Supply Chain: An Approach via Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA)

Multi Objective Supply Chain Network Reconfiguration Under Disruptions

A mathematical modeling approach for supply chain management under disruption and operational uncertainty

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