scholarly journals Combinative distance based assessment (CODAS) framework using logarithmic normalization for multi-criteria decision making

2021 ◽  
Vol 16 (2) ◽  
pp. 321-340
Author(s):  
Sanjib Biswas ◽  
Dragan Pamucar
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Multi Criteria Decision Making ◽  
Extended Version ◽  
Comparative Performance ◽  
Rank Reversal ◽  
Reversal Phenomenon ◽  
Computational Capability ◽  
Transitivity Property

The purpose of this paper is to present an extended Combinative Distance based Assessment (CODAS) framework using logarithmic normalization (LN) scheme. LN is useful in the situations where criteria values differ significantly. This framework is used to carry out a comparative performance based ranking of the popular smartphones in India. The result obtained from this extended version of CODAS method (CODAS-LN) shows consistency with that generated by using some other established multi-criteria decision making (MCDM) approaches. The sensitivity analysis shows considerable stability in the result. Further, it is observed that CODAS-LN is free from rank reversal phenomenon and follows the transitivity property. Findings of the case study suggest that the smartphones with higher computational capability and features rank in top brackets.

scholarly journals Multi-Criteria Decision-Making Method for Sustainable Energy-Saving Retrofit Façade Solutions

2021 ◽  
Vol 13 (23) ◽  
pp. 13168
Author(s):  
Ziortza Egiluz ◽  
Jesús Cuadrado ◽  
Andoni Kortazar ◽  
Ignacio Marcos
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Savings ◽  
Multi Criteria Decision Making ◽  
Effective Energy ◽  
Economic Basis ◽  
Selection Of

The increasing energy consumption levels of buildings within Europe call for controlled consumption and improvements to energy savings and efficiency and effective energy efficiency regulations. However, many aging and energy-inefficient buildings require energetic retrofitting that can employ various façades solutions and insulation materials. The selection of the most sustainable options in each situation therefore requires a decision-making methodology that can be used to prioritize available retrofit solutions based on economic, functional, environmental and social criteria. In this paper, both the methodology and the economic basis of the retrofitting process are presented. The methodology was validated in a case study, and a sensitivity analysis also demonstrated its validity, robustness and stability

scholarly journals A NEW LOGARITHM METHODOLOGY OF ADDITIVE WEIGHTS (LMAW) FOR MULTI-CRITERIA DECISION-MAKING: APPLICATION IN LOGISTICS

2021 ◽  
Vol 19 (3) ◽  
pp. 361
Author(s):  
Dragan Pamučar ◽  
Mališa Žižović ◽  
Sanjib Biswas ◽  
Darko Božanić
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Outcome Variable ◽  
Multi Criteria Decision Making ◽  
Competitive Growth ◽  
Reversal Problem ◽  
Rank Reversal ◽  
Logistics Service Provider ◽  
Operational Metrics

Logistics management has been playing a significant role in ensuring competitive growth of industries and nations. This study proposes a new Multi-Criteria Decision-making (MCDM) framework for evaluating operational efficiency of logistics service provider (LSP). We present a case study of comparative analysis of six leading LSPs in India using our proposed framework. We consider three operational metrics such as annual overhead expense (OE), annual fuel consumption (FC) and cost of delay (CoD, two qualitative indicators such as innovativeness (IN) which basically indicates process innovation and average customer rating (CR)and one outcome variable such as turnover (TO) as the criteria for comparative analysis. The result shows that the final ranking is a combined effect of all criteria. However, it is evident that IN largely influences the ranking. We carry out a comparative analysis of the results obtained from our proposed method with that derived by using existing established frameworks. We find that our method provides consistent results; it is more stable and does not suffer from rank reversal problem.

scholarly journals Extended EDAS Method for Fuzzy Multi-criteria Decision-making: An Application to Supplier Selection

2016 ◽  
Vol 11 (3) ◽  
pp. 358 ◽  
Author(s):  
Mehdi Keshavarz Ghorabaee ◽  
Edmundas Kazimieras Zavadskas ◽  
Maghsoud Amiri ◽  
Zenonas Turskis
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Real World ◽  
Supplier Selection ◽  
Multi Criteria Decision Making ◽  
Fuzzy Environment ◽  
Methods And Techniques ◽  
The Stability ◽  
Real World Problems

In the real-world problems, we are likely confronted with some alternatives that eed to be evaluated with respect to multiple conflicting criteria. Multi-criteria ecision-making (MCDM) refers to making decisions in such a situation. There are any methods and techniques available for solving MCDM problems. The evaluation ased on distance from average solution (EDAS) method is an efficient multi-criteria ecision-making method. Because the uncertainty is usually an inevitable part of he MCDM problems, fuzzy MCDM methods can be very useful for dealing with the eal-world decision-making problems. In this study, we extend the EDAS method o handle the MCDM problems in the fuzzy environment. A case study of supplier election is used to show the procedure of the proposed method and applicability of t. Also, we perform a sensitivity analysis by using simulated weights for criteria to xamine the stability and validity of the results of the proposed method. The results f this study show that the extended fuzzy EDAS method is efficient and has good tability for solving MCDM problems.

scholarly journals Simulation-based multi-criteria decision making: an interactive method with a case study on infectious disease epidemics

2021 ◽  
Author(s):  
Fabian Dunke ◽  
Stefan Nickel
Keyword(s):  
Infectious Disease ◽  
Decision Making ◽  
Sensitivity Analysis ◽  
Parameter Uncertainty ◽  
Multiple Objectives ◽  
Decision Making Process ◽  
Multi Criteria Decision Making ◽  
Analysis Question ◽  
Simulation Based

AbstractWhenever a system needs to be operated by a central decision making authority in the presence of two or more conflicting goals, methods from multi-criteria decision making can help to resolve the trade-offs between these goals. In this work, we devise an interactive simulation-based methodology for planning and deciding in complex dynamic systems subject to multiple objectives and parameter uncertainty. The outline intermittently employs simulation models and global sensitivity analysis methods in order to facilitate the acquisition of system-related knowledge throughout the iterations. Moreover, the decision maker participates in the decision making process by interactively adjusting control variables and system parameters according to a guiding analysis question posed for each iteration. As a result, the overall decision making process is backed up by sensitivity analysis results providing increased confidence in terms of reliability of considered decision alternatives. Using the efficiency concept of Pareto optimality and the sensitivity analysis method of Sobol’ sensitivity indices, the methodology is then instantiated in a case study on planning and deciding in an infectious disease epidemic situation similar to the 2020 coronavirus pandemic. Results show that the presented simulation-based methodology is capable of successfully addressing issues such as system dynamics, parameter uncertainty, and multi-criteria decision making. Hence, it represents a viable tool for supporting decision makers in situations characterized by time dynamics, uncertainty, and multiple objectives.

scholarly journals Application of interval valued fuzzy-rough numbers in multi-criteria decision making: The IVFRN-MAIRCA model

2019 ◽  
Vol 29 (2) ◽  
pp. 221-247 ◽  
Author(s):  
Dragan Pamucar ◽  
Goran Cirovic ◽  
Darko Bozanic
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
High Stability ◽  
Multi Criteria Decision Making ◽  
Analysis Method ◽  
New Approach ◽  
The Given ◽  
Interval Valued ◽  
Selection Of

This paper presents a new approach for the treatment of uncertainty and imprecision based on interval-valued fuzzy-rough numbers (IVFRNs). IVFRNs make a decision making possible using only the internal knowledge from the data, using objective indeterminacy without the need to rely on models of any assumption. Namely, instead of subjectively entering external uncertainties, the structure of the given data is used. Taking into account the given assumptions, we developed an original multi-criteria model based upon the IVFR approach. In the multi-criteria model the traditional MAIRCA (Multi-Attribute Ideal-Real Comparative Analysis) method was modified. The model was tested and validated on a case study, considering selection of the optimal landing operations point for overcoming water obstacles. The sensitivity analysis of the IVFRN MAIRCA model was carried out through 24 scenarios which showed that our results are of a high stability degree.

Multi-Criteria Decision Making for Vulnerability Mapping of Flood Hazard: A Case Study of Pune City

2019 ◽  
Vol 2 (1) ◽  
pp. 41-52
Author(s):  
Nitin Mundhe
Keyword(s):  
Decision Making ◽  
Flood Hazard ◽  
Geographical Information ◽  
Multi Criteria Decision Making ◽  
Flood Hazards ◽  
Very High Frequency ◽  
Flood Vulnerability ◽  
Natural Risk ◽  
The Town

Floods are natural risk with a very high frequency, which causes to environmental, social, economic and human losses. The floods in the town happen mainly due to human made activities about the blockage of natural drainage, haphazard construction of roads, building, and high rainfall intensity. Detailed maps showing flood vulnerability areas are helpful in management of flood hazards. Therefore, present research focused on identifying flood vulnerability zones in the Pune City using multi-criteria decision-making approach in Geographical Information System (GIS) and inputs from remotely sensed imageries. Other input data considered for preparing base maps are census details, City maps, and fieldworks. The Pune City classified in to four flood vulnerability classes essential for flood risk management. About 5 per cent area shows high vulnerability for floods in localities namely Wakdewadi, some part of the Shivajinagar, Sangamwadi, Aundh, and Baner with high risk.

scholarly journals Coupling Fuzzy Multi-Criteria Decision-Making and Clustering Algorithm for MSW Landfill Site Selection (Case Study: Lanzhou, China)

2021 ◽  
Vol 10 (6) ◽  
pp. 403
Author(s):  
Jiamin Liu ◽  
Yueshi Li ◽  
Bin Xiao ◽  
Jizong Jiao
Keyword(s):  
Decision Making ◽  
Clustering Algorithm ◽  
Fuzzy Membership Function ◽  
Multi Criteria Decision Making ◽  
Landfill Site Selection ◽  
Spatial Distribution Characteristics ◽  
Criteria Weights ◽  
Spatial Decision Making ◽  
Complex Decision

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.

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