Resilient food supply chain design: Modelling framework and metaheuristic solution approach

Bottani, Eleonora; Murino, Teresa; Schiavo, Massimo; Akkerman, Renzo

doi:10.1016/j.cie.2019.05.011

Cited by 94 publications

(65 citation statements)

References 52 publications

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“…Neglecting supplier selection as a variable in these models does not offer a holistic approach toward repercussions within the larger supply network. However, when publications do account for vendors, the authors limit the scope of the supply chain or complexity of disruption, such as material scarcity (Gaustad et al 2018;Bottani et al 2019). Gao et al (2019) acknowledge that disruption scenarios with a higher degree of unknowns must limit the supply chain modeled in order to model the supply chain resilience.…”

Section: Modeling Disruptionsmentioning

confidence: 99%

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

2020

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The increasingly global context in which businesses operate supports innovation, but also increases uncertainty around supply chain disruptions. The COVID-19 pandemic clearly shows the lack of resilience in supply chains and the impact that disruptions may have on a global network scale as individual supply chain connections and nodes fail. This cascading failure underscores the need for the network analysis and advanced resilience analytics we find lacking in the existing supply chain literature. This paper reviews supply chain resilience literature that focuses on resilience modeling and quantification and connects the supply chain to other networks, including transportation and command and control. We observe a fast increase in the number of relevant papers (only 47 relevant papers were published in 2007-2016, while 94 were found in 2017-2019). We observe that specific disruption scenarios are used to develop and test supply chain resilience models, while uncertainty associated with threats including consideration of "unknown unknowns" remains rare. Publications that utilize more advanced models often focus just on supply chain networks and exclude associated system components such as transportation and command and control (C2) networks, which creates a gap in the research that needs to be bridged. The common goal of supply chain modeling is to optimize efficiency and reduce costs, but trade-offs of efficiency and leanness with flexibility and resilience may not be fully addressed. We conclude that a comprehensive approach to network resilience quantification encompassing the supply chain in the context of other social and physical networks is needed to address the emerging challenges in the field. The connection to systemic threats, such as disease pandemics, is specifically discussed.

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Section: Modeling Disruptionsmentioning

confidence: 99%

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

2020

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“…The most widely used methodology is analytical, so an analysis of the principal techniques used to manage resilience in the supply chain was generated (Table 5) [11,[143][144][145][146][147][148][149][150][151][152][153][154][155][156][157] Total articles with analytical methodology: 116. Table 6 shows the studies by industry and classifies them according to the methodology used.…”

Section: Descriptive Analysis By Research Methodologymentioning

confidence: 99%

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

2020

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The challenges of global economies foster supply chains to have to increase their processes of collaboration and dependence between their nodes, generating an increase in the level of vulnerability to possible impacts and interruptions in their operations that may affect their sustainability. This has developed an emerging area of interest in supply chain management, considering resilience management as a strategic capability of companies, and causing an increase in this area of research. Additionally, supply chains should deal with the three dimensions of sustainability (economic, environmental, and social dimensions) by incorporating the three types of objectives in their strategy. Thus, there is a need to integrate both resilience and sustainability in supply chain management to increase competitiveness. In this paper, a systematic literature review is undertaken to analyze resilience management and its connection to increase supply chain sustainability. In the review, 232 articles published from 2000 to February 2020 in peer-reviewed journals in the Scopus and ScienceDirect databases are analyzed, classified, and synthesized. With the results, this paper develops a conceptual framework that integrates the fundamental elements for analyzing, measuring, and managing resilience to increase sustainability in the supply chain. Finally, conclusions, limitations, and future research lines are exposed.

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“…Regarding metaheuristics, Bottani et al. [16] employ an Ant Colony Optimization algorithm (ACO), and [64] and [165] propose hybrid metaheuristics as a solution approach: a Taguchi-based memetic algorithm (TMA) for the first case, and a combination among differential evolution algorithm, variable neighborhood search algorithm and game theory (DVG) for the second case. This fact shows the high potential of designing heuristic-based approaches, given that strategic real-world problems might be both NP-hard and contain large-sized instances [2] , [34] , [125] .…”

Section: Main Findings From the Slr Processmentioning

confidence: 99%

Simulation-optimization methods for designing and assessing resilient supply chain networks under uncertainty scenarios: A review

Tordecilla

Juan

Montoya‐Torres

et al. 2021

Simulation Modelling Practice and Theory

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The design of supply chain networks (SCNs) aims at determining the number, location, and capacity of production facilities, as well as the allocation of markets (customers) and suppliers to one or more of these facilities. This paper reviews the existing literature on the use of simulation-optimization methods in the design of resilient SCNs. From this review, we classify some of the many works in the topic according to factors such as their methodology, the approach they use to deal with uncertainty and risk, etc. The paper also identifies several research opportunities, such as the inclusion of multiple criteria (e.g., monetary, environmental, and social dimensions) during the design-optimization process and the convenience of considering hybrid approaches combining metaheuristic algorithms, simulation, and machine learning methods to account for uncertainty and dynamic conditions, respectively.

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Resilient food supply chain design: Modelling framework and metaheuristic solution approach

Cited by 94 publications

References 52 publications

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

Simulation-optimization methods for designing and assessing resilient supply chain networks under uncertainty scenarios: A review

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