Development of flood resilience framework for housing infrastructure system: Integration of best-worst method with evidence theory

Sen, M. K.; Dutta, Subhrajit; Kabir, Golam

doi:10.1016/j.jclepro.2020.125197

Cited by 39 publications

(17 citation statements)

References 61 publications

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“…Huang et al ( 2021 ) propose a Bayesian BWM and modified Ranking Organization Method for Enrichment Evaluations (PROMETHEE)–based airport resilience assessment model. Sen et al ( 2021 ) examine the flood resilience of housing infrastructure system by BWM. Moslem et al ( 2020 ) employed BWM to examine mobility choice alternatives for post COVID-19 era.…”

Section: Proposed Methodologymentioning

confidence: 99%

Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era

Ayyıldız

2021

Environ Sci Pollut Res

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Supply chain organizations should calmly and cautiously take the most accurate and sustainable decisions quickly and put them into practice. It is obvious that traditional time series–based demand and supply planning approaches are insufficient to meet current business needs due to factors such as sharp changes in market and commercial dynamics, pandemics, and natural disasters on the management of green supply chains, especially these days. In the near future, there will be a need for more resilient supply chains with a flexible business models that are not affected by sudden changes and that can make sustainable decisions dynamically. Additionally, all stakeholders must act with a green supply chain approach to conduct production and service activities in a way that causes the least damage to nature. Companies must build more resilient supply chains by considering environmental sensitivities to compete in the market and ensure their continuity. In this context, the green supply chains should be evaluated according to their resilience. For this purpose, Supply Chain Operations Reference (SCOR) model is extended with novel performance attributes to evaluate resilience of green supply chains in this study. The SCOR-embedded novel green supply chain resilience evaluation model is structured as a three-level performance attribute hierarchical structure. Then, the model is handled as a multi-criteria decision-making problem to determine importance of the performance attributes. Best Worst Method integrated Interval Valued Intuitionistic Fuzzy Analytic Hierarchy Process is used to determine the importance of performance attributes. Most important performance attributes are determined in each level of hierarchy. According to results, organizational factors play a key role to build more resilient supply chains. Especially, integrated systems are required for supply chain resilience.

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Section: Proposed Methodologymentioning

confidence: 99%

Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era

Ayyıldız

2021

Environ Sci Pollut Res

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“…Resilience essentially depends on two crucial characteristics: infrastructure reliability and recovery [11,25]. Therefore, resilience is connected to the reliability and recovery of the infrastructure, which is shown in Figure 3.…”

Section: Stormwater Infrastructure Resilience's Hierarchical Model De...mentioning

confidence: 99%

Earthquake Resilience Framework for a Stormwater Pipe Infrastructure System Integrating the Best Worst Method and Dempster–Shafer Theory

Garshasbi

Kabir

2022

Sustainability

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Stormwater pipe infrastructure is a fundamental requirement of any nation, but pipes can be damaged in natural disasters. Consequently, evaluating the resilience of stormwater infrastructure to earthquake damage is an essential duty for any city because it outlines the capability to recover from a disaster after the event. The resilience quantification process needs various data types from various sources, and uncertainty and partial data may be included. This study recommends a resilience assessment framework for stormwater pipe infrastructure facing earthquake hazards using Hierarchical Evidential Reasoning (HER) on the basis of the Dempster–Shafer (D-S) theory. The developed framework was implemented in the City of Regina, SK, Canada to quantify the resilience of the stormwater pipe infrastructure. First, various resilience factors were identified from the literature. Based on experts’ judgment, the weight of these factors was determined using the Best Worst Method (BWM). After that, the resilience was determined using the D–S theory. Finally, sensitivity analysis was conducted to examine the sensitivity of the factors of the recommended hierarchical stormwater infrastructure resilience model. The recommended earthquake resilience assessment model produced satisfying outcomes, which showed the condition state of resilience with the degree of uncertainty.

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“…Chen et al 68 proposed a hybrid BWM method under a rough fuzzy environment. A belief‐based BWM considering the level of belief of preferences is proposed by Liang et al 69 Sen et al 70 applied the combination of BWM and Dempster–Shafer theory for a flood resilience development model for housing infrastructure. A risk‐based BWM based on R‐numbers is applied in a project selection problem in a healthcare firm 71 .…”

Section: Literature Surveymentioning

confidence: 99%

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Hasan¹,

Ashraf

Khan

2021

Int J of Intelligent Sys

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The best‐worst method (BWM) is a multi‐criteria decision‐making (MCDM) approach for solving several types of real‐life decision‐making problems. The basic BWM determines the priority order by pairwise comparisons of the best and worst criteria. The strength of the preference assigned via numerical value for linguistic interpretations of relative comparisons ranges from 1 to 9, representing preferences among the criterion. However, the amount of strength is entirely dependent on the choice of the decision‐makers. Though expert's opinions may differ due to various reasons such as incomplete information, lack of knowledge, ambiguity in linguistic terms, and so forth. Therefore, it is highly likely that the expert may provide multiple viewpoints for the preferences values. Thus, this study proposes a novel extension of the BWM named the multi‐choice best‐worst method (MCBWM), dealing with the concept of multiple choices of preference relations to compare the criterion. The MCBWM overcomes the limitation of BWM, where the pairwise preferences in the comparisons are multi‐choice parameters rather than single parametric values. Multiple real‐world MCDM applications are illustrated in experimental studies to show the quality, performance, and applicability of our proposed MCBWM. A detailed comparative analysis of the proposed approach has been done with the well‐known existing decision‐making techniques and their optimal results are compared. The proposed method offers a new direction for the MCDM approaches for solving real‐life problems.

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Development of flood resilience framework for housing infrastructure system: Integration of best-worst method with evidence theory

Cited by 39 publications

References 61 publications

Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era

Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era

Earthquake Resilience Framework for a Stormwater Pipe Infrastructure System Integrating the Best Worst Method and Dempster–Shafer Theory

Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

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