scholarly journals A Multiple Criteria Risk Analysis Model and a Case Study in Metal Industry

2020 ◽  
Vol 08 (05) ◽  
pp. 2048-2070
Author(s):  
Safinaz Esra Ciftci ◽  
Feyzan Arikan
Author(s):  
Adriana Goulart dos Santos ◽  
Rodrigo Machado

Abstract This article studied the location of dry ports from the perspective of reducing impacts caused by seaport activities on the urban environment. The main objective was to construct a model based on multiple-criteria decision analysis coupled with the geographical information system for selecting areas subject to the location of dry ports. An important point was the definition of restriction and factor criteria for the preparation of this model. The distance from the seaport was defined as the most relevant criterion, followed by the road hierarchy network, population density, vegetation, and declivity, respectively. The predominant restrictive criteria were: permanent conservation areas and non-building zones. For the validation of the model presented, it was necessary to perform a case study on a city located near a seaport, and that has been legalized seaport activities in its legislation. The result showed that the areas nearest to the port, with less density of household units, and located near main roadways are the most feasible for location of dry ports. It was proven that the usage of multi-criteria analysis for selecting areas subject to the location of dry ports can be a manner for added support in the preparation of master plans for cities surrounded by seaport areas.


Algorithms ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 163
Author(s):  
Seyed Hamed Fateminia ◽  
Vuppuluri Sumati ◽  
Aminah Robinson Fayek

Determining contingency reserve is critical to project risk management. Classic methods of determining contingency reserve significantly rely on historical data and fail to effectively incorporate certain types of uncertainties such as vagueness, ambiguity, and subjectivity. In this paper, an interval type-2 fuzzy risk analysis model (IT2FRAM) is introduced in order to determine the contingency reserve. In IT2FRAM, the membership functions for the linguistic terms used to describe the probability, impact of risk and the opportunity events are developed, optimized, and aggregated using interval type-2 fuzzy sets and the principle of justifiable granularity. IT2FRAM is an extension of a fuzzy arithmetic-based risk analysis method which considers such uncertainties and addresses the limitations of probabilistic and deterministic techniques of contingency determination methods. The contribution of IT2FRAM is that it considers the opinions of several subject matter experts to develop the membership functions of linguistic terms. Moreover, the effect of outlier opinions in developing the membership functions of linguistic terms are reduced. IT2FRAM also enables the aggregation of non-linear membership functions into trapezoidal membership functions. A hypothetical case study is presented in order to illustrate the application of IT2FRAM in Fuzzy Risk Analyzer© (FRA©), a risk analysis software.


Heliyon ◽  
2021 ◽  
Vol 7 (5) ◽  
pp. e06911
Author(s):  
Peiman Dadkani ◽  
Esmatullah Noorzai ◽  
AmirHossein Ghanbari ◽  
Ali Gharib

2015 ◽  
Vol 22 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Önder Ökmen ◽  
Ahmet Öztaş

Purpose – Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses. Design/methodology/approach – The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results. Findings – The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies. Originality/value – Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.


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