Techniques to model uncertain input data of multi‐criteria decision‐making problems: a literature review

2018 ◽  
Vol 28 (2) ◽  
pp. 523-559 ◽  
Author(s):  
Renata Pelissari ◽  
Maria Celia Oliveira ◽  
Alvaro J. Abackerli ◽  
Sarah Ben‐Amor ◽  
Maria Rita Pontes Assumpção
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Input Data ◽  
Multi Criteria Decision Making ◽  
Uncertain Input ◽  
Uncertain Input Data

scholarly journals A Systematic Literature Review of Multi-Criteria Decision-Making Methods for Sustainable Selection of Insulation Materials in Buildings

2021 ◽  
Vol 13 (2) ◽  
pp. 737
Author(s):  
Indre Siksnelyte-Butkiene ◽  
Dalia Streimikiene ◽  
Tomas Balezentis ◽  
Virgilijus Skulskis
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Energy Demand ◽  
Energy Performance ◽  
Future Research ◽  
Multi Criteria Decision Making ◽  
Insulation Materials ◽  
Advantages And Disadvantages ◽  
Selection Of

The European Commission has recently adopted the Renovation Wave Strategy, aiming at the improvement of the energy performance of buildings. The strategy aims to at least double renovation rates in the next ten years and make sure that renovations lead to higher energy and resource efficiency. The choice of appropriate thermal insulation materials is one of the simplest and, at the same time, the most popular strategies that effectively reduce the energy demand of buildings. Today, the spectrum of insulation materials is quite wide, and each material has its own specific characteristics. It is recognized that the selection of materials is one of the most challenging and difficult steps of a building project. This paper aims to give an in-depth view of existing multi-criteria decision-making (MCDM) applications for the selection of insulation materials and to provide major insights in order to simplify the process of methods and criteria selection for future research. A systematic literature review is performed based on the Search, Appraisal, Synthesis and Analysis (SALSA) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In order to determine which MCDM method is the most appropriate for different questions, the main advantages and disadvantages of different methods are provided.

Preparation of Sub-Criteria for Mathematical Modeling of Multi-Criteria Decision Making

2014 ◽  
Vol 1020 ◽  
pp. 765-768
Author(s):  
Eva Berankova ◽  
František Kuda ◽  
Stanislav Endel
Keyword(s):  
Decision Making ◽  
Public Service ◽  
Input Data ◽  
Decision Making Process ◽  
Multi Criteria Decision Making ◽  
Individual Selection ◽  
Qualitative And Quantitative ◽  
Data Analyses ◽  
Quantitative Characters ◽  
The Subject

The subject of this paper is to evaluate criteria in the decision-making process for choosing new usable office facilities in light of a big company or public service seeking for new usable office facilities. The criteria defining the requirements for individual selection variants enter into this decision-making process. These criteria have qualitative and quantitative characters. In order to model the criteria, it is desirable that their values are standardized. The method of standardization of these criteria is given in this paper. In this paper, attention is paid to the decision-making process in the course of choosing new usable facilities in administration objects. This decision-making process is based on input data analyses and on conclusions for a certain selection variant resulting from them.

A Fuzzy Approach to Disaster Modeling

2013 ◽  
pp. 1038-1055
Author(s):  
Jan Stoklasa
Keyword(s):  
Disaster Response ◽  
Initial Phase ◽  
Input Data ◽  
Fuzzy Model ◽  
Fuzzy Rule ◽  
Linguistic Variables ◽  
Rescue Services ◽  
Uncertain Input ◽  
Uncertain Input Data ◽  
Rule Bases

The decision making process of the Emergency Medical Rescue Services (EMRS) operations centre during disasters involves a significant amount of uncertainty. Decisions need to be made quickly, and no mistakes are tolerable, particularly in the case of disasters resulting in a large number of injured people. A multiphase linguistic fuzzy model is introduced to assist the operator during the initial phase of the medical disaster response. Based on uncertain input data, estimating the severity of the disaster, the number of injured people, and the amount of forces and resources needed to successfully deal with the situation is possible. The need for reinforcements is also considered. Fuzzy numbers, linguistic variables and fuzzy rule bases are applied to deal with the uncertainty. Outputs provided by the model (severity of the disaster, number of reinforcements needed etc.) are available both as fuzzy sets (for the purposes of disaster planning) and linguistic terms (for emergency call evaluation purposes).

Design and Implementation of a Fuzzy Inference Model for Mapping the Sustainability of Energy Crops

2017 ◽  
pp. 657-678
Author(s):  
Fausto Cavallaro ◽  
Luigi Ciraolo
Keyword(s):  
Environmental Sustainability ◽  
Input Data ◽  
Fuzzy Inference ◽  
Renewable Energy Sources ◽  
Energy Crops ◽  
Environmental Evaluation ◽  
Uncertain Input ◽  
Inference Systems ◽  
Uncertain Input Data ◽  
Biomass For Energy

Energy crops are positioned as the most promising renewable energy sources. Over recent years, the use of biomass has been growing significantly, especially in countries that have made a strong commitment to renewable sources in their energy policies. One of the aspects of the use of biomass for energy is that it is still controversial with regard to full environmental sustainability. Unfortunately, the existing environmental evaluation tools in many cases are unable to manage uncertain input data. Fuzzy-set-based methods, instead, have proved to be able to deal with uncertainty in environmental topics. The idea of this chapter is to reproduce a solution by decoding it from the domain of knowledge with the calculus of fuzzy “if-then” rules. A methodology based on Fuzzy Inference Systems (FIS) is proposed to assess the environmental sustainability of biomass.

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