scholarly journals From Goal Programming for Continuous Multi-Criteria Optimization to the Target Decision Rule for Mixed Uncertain Problems

Entropy ◽  
2021 ◽  
Vol 24 (1) ◽  
pp. 51
Author(s):  
Helena Gaspars-Wieloch
Keyword(s):  
Decision Making ◽  
Decision Rule ◽  
Goal Programming ◽  
Decision Makers ◽  
Decision Making Under Uncertainty ◽  
Multi Criteria Decision Making ◽  
The Novel ◽  
Continuous Version ◽  
Novel Approach

Goal programming (GP) is applied to the discrete and continuous version of multi-criteria optimization. Recently, some essential analogies between multi-criteria decision making under certainty (M-DMC) and scenario-based one-criterion decision making under uncertainty (1-DMU) have been revealed in the literature. The aforementioned similarities allow the adjustment of GP to an entirely new domain. The aim of the paper is to create a new decision rule for mixed uncertain problems on the basis of the GP methodology. The procedure can be used by pessimists, optimists and moderate decision makers. It is designed for one-shot decisions. One of the significant advantages of the novel approach is related to the possibility to analyze neutral criteria, which are not directly taken into account in existing classical procedures developed for 1-DMU.

scholarly journals A New Application for the Goal Programming—The Target Decision Rule for Uncertain Problems

2020 ◽  
Vol 13 (11) ◽  
pp. 280
Author(s):  
Helena Gaspars-Wieloch
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Decision Rule ◽  
Goal Programming ◽  
The Other ◽  
Decision Making Under Uncertainty ◽  
Multi Criteria Decision Making ◽  
Other Hand ◽  
Novel Method

The goal programming (GP) is a well-known approach applied to multi-criteria decision making (M-DM). It has been used in many domains and the literature offers diverse extensions of this procedure. On the other hand, so far, some evident analogies between M-DM under certainty and scenario-based one-criterion decision making under uncertainty (1-DMU) have not been revealed in the literature. These similarities give the possibility to adjust the goal programming to an entirely new domain. The purpose of the paper is to create a novel method for uncertain problems on the basis of the GP ideas. In order to achieve this aim we carefully examine the analogies occurring between the structures of both issues (M-DM and 1-DMU). We also analyze some differences resulting from a different interpretation of the data. By analogy to the goal programming, four hybrids for 1-DMU are formulated. They differ from each other in terms of the type of the decision maker considered (pessimist, optimist, moderate). The new decision rule may be helpful when solving uncertain problems since it is especially designed for neutral criteria, which are not taken into account in existing procedures developed for 1-DMU.

Novel Stable Approach with Probability Distribution for Multi-Criteria Decision-Making Problems of Multi-Valued Neutrosophic Sets

2020 ◽  
Vol 19 (05) ◽  
pp. 1271-1292
Author(s):  
Xu Libo ◽  
Li Xingsen ◽  
Cui Honglei
Keyword(s):  
Decision Making ◽  
Probability Distribution ◽  
Dynamic Change ◽  
Distribution Functions ◽  
Transformation Operator ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Neutrosophic Sets ◽  
Dependent Function ◽  
Novel Approach

In this paper, a novel approach and framework based on interval-dependent degree and probability distribution for multi-criteria decision-making problems with multi-valued neutrosophic sets (MVNSs) is proposed. First, a simplified dependent function and distribution function are given and integrated into a concise formula, which is called the interval-dependent function and contains interval computing and probability distribution information in an interval. Then a transformation operator is defined and it is shown how to convert MVNSs into an interval set. Subsequently, the interval-dependent function with the probability distribution of MVNSs is deduced. Finally, an example and comparative analysis are provided to verify the feasibility and effectiveness of the proposed method. In addition, uncertainty analysis, which reflects the dynamic change of the ranking result with decision-makers’ preferences, is performed by setting different distribution functions, which increases the reliability and accuracy of the proposed method.

scholarly journals Decision Support Algorithm for Selecting an Antivirus Mask over COVID-19 Pandemic under Spherical Normal Fuzzy Environment

2020 ◽  
Vol 17 (10) ◽  
pp. 3407 ◽  
Author(s):  
Zaoli Yang ◽  
Xin Li ◽  
Harish Garg ◽  
Meng Qi
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Human Cognition ◽  
Multi Criteria Decision Making ◽  
The Novel ◽  
Accuracy Function ◽  
Bonferroni Mean ◽  
Fuzzy Environment ◽  
Novel Concept

With the rapid outbreak of COVID-19, most people are facing antivirus mask shortages. Therefore, it is necessary to reasonably select antivirus masks and optimize the use of them for everyone. However, the uncertainty of the effects of COVID-19 and limits of human cognition add to the difficulty for decision makers to perfectly realize the purpose. To maximize the utility of the antivirus mask, we proposed a decision support algorithm based on the novel concept of the spherical normal fuzzy (SpNoF) set. In it, firstly, we analyzed the new score and accuracy function, improved operational rules, and their properties. Then, in line with these operations, we developed the SpNoF Bonferroni mean operator and the weighted Bonferroni mean operator, some properties of which are also examined. Furthermore, we established a multi-criteria decision-making method, based on the proposed operators, with SpNoF information. Finally, a numerical example on antivirus mask selection over the COVID-19 pandemic was given to verify the practicability of the proposed method, which the sensitive and comparative analysis was based on and was conducted to demonstrate the availability and superiority of our method.

scholarly journals An Overview of Multi-Criteria Decision-Making Methods in Dealing with Sustainable Energy Development Issues

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2754 ◽  
Author(s):  
Indre Siksnelyte ◽  
Edmundas Zavadskas ◽  
Dalia Streimikiene ◽  
Deepak Sharma
Keyword(s):  
Decision Making ◽  
Swot Analysis ◽  
Sustainable Energy ◽  
Energy Development ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Energy Sustainability ◽  
Widespread Application ◽  
Sustainability Problems ◽  
Scientific Achievements

The measurement of sustainability is actively used today as one of the main preventative instruments in order to reduce the decline of the environment. Sustainable decision-making in solving energy issues can be supported and contradictory effects can be evaluated by scientific achievements of multi-criteria decision-making (MCDM) techniques. The main goal of this paper is to overview the application of decision-making methods in dealing with sustainable energy development issues. In this study, 105 published papers from the Web of Science Core Collection (WSCC) database are selected and reviewed, from 2004 to 2017, related to energy sustainability issues and MCDM methods. All the selected papers were categorized into 9 fields by the application area and into 10 fields by the used method. After the categorization of the scientific articles and detailed analysis, SWOT analysis of MCDM approaches in dealing with sustainable energy development issues is provided. The widespread application and use of MCDM methods confirm that MCDM methods can help decision-makers in solving energy sustainability problems and are highly popular and used in practice.

Some Conflicting Results in the Analytic Hierarchy Process

2019 ◽  
Vol 18 (02) ◽  
pp. 465-486 ◽  
Author(s):  
Ardalan Bafahm ◽  
Minghe Sun
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Decision Makers ◽  
Unexpected Result ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Preference Relations ◽  
The Analytic Hierarchy Process ◽  
Hierarchy Process

The analytic hierarchy process (AHP) has been believed to be one of the most pragmatic and widely accepted methods for multi-criteria decision making. However, there have been various criticisms of this method within the last four decades. In this study, the results of AHP contradicting common expectations are examined for both the distributive and ideal modes. Specifically, conflicting priorities, conflicting decisions, and conflicting preference relations are investigated. A decision-making scenario is used throughout the paper and an illustrative example constructed from the decision-making scenario is provided to demonstrate each of the conflicting results recommended by AHP. With a parametric formulation of each unexpected result, the possibility of unexpected results of AHP is generalized irrespective of applying the distributive or ideal mode. The logic and causes of these contradictions are also analyzed. This study shows that AHP is not always reliable, and could lead the decision makers towards incorrect decisions.

Multi-Criteria Decision-Making Model using Intuitionistic Fuzzy Entropy and Variable Weight Theory

Mekatronika ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 18-25
Author(s):  
Omar Ayasrah ◽  
Faiz Mohd Turan
Keyword(s):  
Decision Making ◽  
Fuzzy Entropy ◽  
Decision Makers ◽  
Entropy Measure ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Variable Weight ◽  
Intuitionistic Fuzzy Entropy ◽  
Perform Sensitivity Analysis ◽  
Almost All

The aim of this research is to develop a new multi-criteria decision-making method that integrates an intuitionistic fuzzy entropy measure and variable weight theory to be implemented in different fields to provide a solution for MCDM problems when the available information is incomplete. A limited number of studies have considered determining decision maker’s weights by performing objective techniques, and almost all of these researches detected a constant weights for the decision makers. In addition, most of the MCDM studies were not formulated to perform sensitivity analysis. The new method is based on the TOPSIS model with an intuitionistic fuzzy entropy measure in the exponential-related function form and the engagement of the variable weight theory to determine weights for the decision-makers that vary as per attibutes. Lastly, a mathematical model was developed in this research to be as an input for developing the mobile-aplication based method in future for virtual use of the new MCDM method.

scholarly journals Toward Better Design-Related Decision Making: A Proposal of an Advanced OODA Loop

2019 ◽  
Vol 1 (1) ◽  
pp. 2387-2396
Author(s):  
Mattia Vettorello ◽  
Boris Eisenbart ◽  
Charlie Ranscombe
Keyword(s):  
Decision Making ◽  
Divergent Thinking ◽  
Abductive Reasoning ◽  
Decision Makers ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Decision Making Under Uncertainty ◽  
Alternative Strategies ◽  
Left Behind ◽  
Lateral Thinking

AbstractTo be successful in innovation, organisations need to be dynamically adaptable to novel situations to avoid getting ‘left behind’. Yet, they face vast uncertainties stemming from unforeseeable technological shifts or future user and market behaviour, making strategic decision-making on innovation an extremely difficult task. Decision-makers thus increasingly try to control or shape the future, rather than foresee it. This includes thinking ahead and generating potential pathways that will make an innovation viable. This captures the essence of designerly ways of thinking in reasoning toward ‘what might be’. Extant literature has been reviewed that discusses alternative strategies how this future-oriented thinking can be applied to become better at selecting novel ideas for development. We observe parallels between divergent thinking, abductive reasoning, analogising and lateral thinking suggested by different authors in this process. The paper continues to propose how these key mechanisms can be embedded within an existing framework for decision-making under uncertainty, the ‘OODA Loop’, which has seen increasing uptake in such decision-making scenarios.

Goal Programming and Its Variants

2011 ◽  
pp. 410-417
Author(s):  
John Wang ◽  
Dajin Wang ◽  
Aihua Li
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Goal Programming ◽  
Multicriteria Decision Making ◽  
Industrial Applications ◽  
Multiple Objective ◽  
Multi Criteria Decision Making ◽  
Powerful Method ◽  
Noticeable Increase ◽  
New Type

Within the realm of multicriteria decision making (MCDM) exists a powerful method for solving problems with multiple objectives. Goal programming (GP) was the first multiple-objective technique presented in the literature (Dowlatshahi, 2001). The premise of GP traces its origin back to a linear programming study on executive compensation in 1955 by Charnes, Cooper, and Ferguson even though the specific name did not appear in publications until the 1961 textbook entitled Management Models and Industrial Applications of Linear Programming, also by Charnes and Cooper (Schniederjans, 1995). Initial applications of this new type of modeling technique demonstrated its potential for a variety of applications in numerous different areas. Until the middle of the 1970s, GP applications reported in the literature were few and far between. Since that time, primarily due to influential works by Lee and Ignizio, a noticeable increase of published GP applications and technical improvements has been recognized. The number of case studies, along with the range of fields, to which GP has been and still is being applied is impressive, as shown in surveys by Romero (1991) and Aouni and Kettani (2001). It can be said that GP has been, and still is, the “most widely used multi-criteria decision making technique” (Tamiz, Jones, & Romero, 1998, p. 570).

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