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Land Evaluation: A General Perspective
Published in Abrar Yousuf, Manmohanjit Singh, Watershed Hydrology, Management and Modeling, 2019
K Karthikeyan, Nirmal Kumar, Abrar Yousuf, Balkrishna S Bhople, Pushpanjali, RK Naitam
MCDA provides an ample collection of techniques and procedures for frame working decision problems, and designing, evaluating and prioritizing alternative decisions. Problems that are multi-dimensional in nature can be tackled with this approach very efficiently. MCDA is used to combine qualitative and quantitative criteria and to specify the degree and nature of the relationships between those criteria in order to support spatial decision making. The main purpose of the MCDA techniques is to investigate a number of alternatives in the light of multiple criteria and conflicting objectives (Voogd 1983). In order to carry out that, it is necessary to generate compromise alternatives and a ranking of alternatives according to their degree of attractiveness (Janssen and Rietveld 1990).
Managing radioactive waste safely
Published in Matthew Cotton, Nuclear Waste Politics, 2017
The MCDA approach works best where decision-makers can compare options that are directly comparable, and it is harder to apply MCDA to strategic issues where the options are not directly comparable i.e. have varying attributes, complexities and uncertainties, incomplete data, or where relative performance is derived from subjective assessment. In CoRWM’s case, for example, they could not easily address what the main discriminator was between the long-term storage of radioactive waste and its disposal (i.e. long-term safety beyond the lifetime of the storage facility) (Collier, 2006). In short, technical criteria are relatively easy to compare using the MCDA approach, but other socio-economic and ethical criteria were not because they require other forms of judgement not adequately catered for in the approach.
multi-criteria decision analysis of water demand management options for puerto ayora
Published in Maria Fernanda Reyes Perez, Water Supply and Demand Management in the lápagos: A Case Study of Santa Cruz Island, 2017
The MCDA encompasses an integrated and complete assessment of multiple suggested alternatives, with a set of tools for any decision making process. These analyses comprise of applied mathematical algorithms that evaluate a collection of different values and factors. The evaluation is usually carried out on problems with conflicting goals, high uncertainty, different forms of data and information, multiple interests and perspectives, and complex biophysical and socio-economic systems (Wang et al. 2009). The ultimate goal of this approach is to define the most feasible and sustainable solution of a certain issue at a low cost and considering all preferences of the participants (Linkov et al. 2006).
Alignment of port policy to the context of the Physical Internet
Published in Maritime Policy & Management, 2023
Patrick B.M. Fahim, Gerjan Mientjes, Jafar Rezaei, Arjan van Binsbergen, Benoit Montreuil, Lorant Tavasszy
MCDA is a sub-field of operations research where multiple decision alternatives are analyzed with respect to multiple (often conflicting) decision criteria. Among several MCDA methods, we choose the BWM. It is a data-efficient method and has proven to produce consistent and reliable results (Rezaei 2015). Through the initial selection of the best and worst criteria, to which the other criteria are compared, BWM is structured, easily executable, and time-efficient. By means of its pairwise comparisons, the BWM also helps decision-makers to gain additional valuable insights. Moreover, through the use of only integers, fundamental distance problems which might occur with the use of fractions in pairwise comparisons can be prevented (Rezaei 2015). Finally, the use of two opposite references (best and worst) mitigates a potential anchoring bias of the respondent (Rezaei 2020).
The mathematical models as a decision support tool for the oil transportation business: A case study of an oil business in Thailand
Published in Cogent Engineering, 2022
Manop Donmuen, Komkrit Pitiruek
MCDA is a multi-objective decision-making procedure. The aim of MCDA is to help identify a better solution depending on the situation and the decision maker’s area of expertise. MCDA methods such as Simple Additive Weighting (SAW; Dobrovolskienė & Pozniak, 2021; Sam’An et al., 2018; Zhao et al., 2021), Analysis Hierarchy Process (AHP), and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS; Akgün & Erdal, 2019) have been adopted. This research considered two factors: the shipping cost and truck utilization. Therefore, SAW was selected as the criterion for decision-making. This method used weights and , which had values ranging from 0.1–0.9. These weights were used to compute the value function for evaluating the ranking and to select the best value function of the traditional model and proposed models. The best choice identified by the MCDA was the lowest value. The MCDA technique is explained as follows:
Evaluation of Retrofitting Techniques for Historical Adobe Constructions Using a multi-criteria Decision Analysis: The Case Study of Chile
Published in International Journal of Architectural Heritage, 2022
Pilar Baquedano Juliá, Stefania Stellacci, Elisa Poletti
MCDA has so far been little explored in heritage reuse and retrofitting techniques (Caterino et al. 2008; Gentile and Galasso 2021), and the selection of the best multi-criteria tool is still controversial. Several scholars have extensively addressed a MCDA method selection framework (Ishizaka and Nemery 2013; Wątróbski et al. 2019), but decision-makers (DMs) or analysts usually choose the method that they are familiar with (Yan Li & Thomas, 2014). The most common MCDA are AHP (Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), MAUT (Multi-Attribute Utility Theory), and MACBETH. This latter method was chosen in this study for its efficiency, number of applications, and strict check for consistency (Ishizaka and Nemery 2013). Above all, MACBETH was chosen for its ability to incorporate a large number of preferences (or subjective evaluations) through pairwise comparison judgments. Its approach is based on synthesizing criteria, where a low score for one criterion may be compensated by high score for another criterion (Roy 2005; Vincke 1992).