A MODEL BASED ON INFLUENCE DIAGRAMS FOR MULTI-CRITERIA DECISION-MAKING

2012 ◽  
Vol 21 (04) ◽  
pp. 1250018 ◽  
Author(s):  
KARIMA SEDKI ◽  
VÉRONIQUE DELCROIX
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Decision Problem ◽  
Expert Knowledge ◽  
External Factors ◽  
Influence Diagrams ◽  
Multi Criteria Decision Making ◽  
Model Based ◽  
Decision Variables ◽  
Other Information

In this paper, we focus on multi-criteria decision-making problems. We propose a model based on influence diagrams; this model is able to handle uncertainty, represent interdependencies among the different decision variables and facilitate communication between the decision-maker and the analyst. The particular structure of the proposed model makes it possible to take into account the alternatives described by an attribute set, the decision-maker's characteristics and preferences, and other information (e.g., internal or external factors) that influence the decision. Modeling the decision problem in terms of influence diagrams requires a lot of work to gather expert knowledge. However, once the model is built, it can be easily and efficiently used for different instances of the decision problem. In fact, using our model simply requires entering some basic information, such as the values of internal or external factors and the decision-maker's characteristics. Our model also defines the importance of each criterion in terms of what is known about the decision maker, the quality index and the utility of each alternative.

New Einstein Hybrid Aggregation Operators for Intuitionistic Fuzzy Sets and Applications in Multi-Criteria Decision-Making

2019 ◽  
pp. 252-283
Author(s):  
Bhagawati Prasad Joshi ◽  
Abhay Kumar
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Decision Maker ◽  
Intuitionistic Fuzzy Sets ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
Multi Criteria Decision Making ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Decision Making Processes

The fusion of multidimensional intuitionistic fuzzy information plays an important part in decision making processes under an intuitionistic fuzzy environment. In this chapter, it is observed that existing intuitionistic fuzzy Einstein hybrid aggregation operators do not follow the idempotency and boundedness. This leads to sometimes illogical and even absurd results to the decision maker. Hence, some new intuitionistic fuzzy Einstein hybrid aggregation operators such as the new intuitionistic fuzzy Einstein hybrid weighted averaging (IFEHWA) and the new intuitionistic fuzzy Einstein hybrid weighted geometric (IFEHWG) were developed. The new IFEHWA and IFEHWG operators can weigh the arguments as well as their ordered positions the same as the intuitionistic fuzzy Einstein hybrid aggregation operators do. Further, it is validated that the defined operators are idempotent, bounded, monotonic and commutative. Then, based on the developed approach, a multi-criteria decision-making (MCDM) procedure is given. Finally, a numerical example is conducted to demonstrate the proposed method effectively.

Multi Criteria Decision Making Enhancing Sustainable Energy Management

2015 ◽  
Vol 805 ◽  
pp. 32-37
Author(s):  
Johannes Boehner
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Energy Efficiency ◽  
Energy Management ◽  
Expert Knowledge ◽  
Energy Costs ◽  
Multi Criteria Decision Making ◽  
Manufacturing Costs ◽  
Discrete Manufacturing ◽  
Energy Optimisation

Establishing energy management in manufacturing major challenge means to increase the energy efficiency of machinery in existing and future processes leading to both, a reduction of energy costs as well as to a reduction of the manufacturing-process-related environmental impacts. Therefore we developed a procedure to prioritize existing machinery for detailed machine examination in order to create a sustainable approach for machine operating companies to prioritise its assets for energy optimisation projects. By using fuzzy logic as method of artificial intelligence nominal and utilisation machinery data as well as inhouse expert knowledge is considered to enhance multi criteria decision making both. Applying this methodology in a series of industrial case studies in discrete manufacturing costs savings of up to 40 percent were realised.

scholarly journals An Essential Analogy Between Coherent Previsions of Random Gains and Well-Behaved Preferences

2019 ◽  
Vol 8 (3) ◽  
pp. 46
Author(s):  
Angelini Pierpaolo ◽  
Angela De Sanctis
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Convex Set ◽  
Choice Model ◽  
Risk Averse ◽  
Two Dimensional ◽  
Unified Approach ◽  
Model Based ◽  
Random Gain ◽  
Economic Criteria

We deal with a unified approach to an integrated and simplified formulation of the decision-making theory in its two subjective components, probability and utility. We show a choice model based on an application of fundamental microeconomic principles to the two-dimensional convex set of all coherent previsions of two random gains. Such a model is well-founded because we find out an analogy between properties of well-behaved preferences and the ones of coherent previsions of random gains. Coherence properties of the notion of price or prevision of a random gain are based on economic criteria of the decision-making theory. In particular, additivity property of price tells us that our decision-maker is not risk-averse but he is risk-neutral. Therefore, the certain gain equivalent to a random gain coincides with a coherent price of this random gain.

scholarly journals NORMALIZED WEIGHTED GEOMETRIC BONFERRONI MEAN OPERATOR OF INTERVAL ROUGH NUMBERS – APPLICATION IN INTERVAL ROUGH DEMATEL-COPRAS

2018 ◽  
Vol 16 (2) ◽  
pp. 171 ◽  
Author(s):  
Dragan Pamučar ◽  
Darko Božanić ◽  
Vesko Lukovac ◽  
Nenad Komazec
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Multi Criteria Decision Making ◽  
Expert Evaluation ◽  
New Approach ◽  
Bonferroni Mean ◽  
Optimal Direction ◽  
Operational Information ◽  
Geometric Bonferroni Mean ◽  
Selection Of

This paper presents a new approach to the treatment of uncertainty and imprecision in multi-criteria decision-making based on interval rough numbers (IRN). The IRN-based approach provides decision-making using only internal knowledge for the data and operational information of a decision-maker. A new normalized weighted geometric Bonferroni mean operator is developed on the basis of the IRN for the aggregation of the IRN (IRNWGBM). Testing of the IRNWGBM operator is performed through the application in a hybrid IR-DEMATEL-COPRAS multi-criteria model which is tested on real case of selection of optimal direction for the creation of a temporary military route. The first part of hybrid model is the IRN DEMATEL model, which provides objective expert evaluation of criteria under the conditions of uncertainty and imprecision. In the second part of the model, the evaluation is carried out using the new interval rough COPRAS technique.

Different decision tree induction strategies for a medical decision problem

Open Medicine ◽  
2012 ◽  
Vol 7 (2) ◽  
pp. 183-193 ◽  
Author(s):  
Robert Burduk ◽  
Michal Wozniak
Keyword(s):  
Decision Making ◽  
Abdominal Pain ◽  
Decision Tree ◽  
Decision Problem ◽  
Acute Abdominal Pain ◽  
Expert Knowledge ◽  
Computer Experiments ◽  
Medical Decision ◽  
Bayes Decision Theory ◽  
Learning Set

AbstractThe paper presents a comparative study of selected recognition methods for the medical decision problem -acute abdominal pain diagnosis. We consider if it is worth using expert knowledge and learning set at the same time. The article shows two groups of decision tree approaches to the problem under consideration. The first does not use expert knowledge and generates classifier only on the basis of learning set. The second approach utilizes expert knowledge for specifying the decision tree structure and learning set for determining mode of decision making in each node based on Bayes decision theory. All classifiers are evaluated on the basis of computer experiments.

scholarly journals Multi-Criteria Decision Making Method with Belief Preference Relations

2014 ◽  
Vol 22 (04) ◽  
pp. 573-590 ◽  
Author(s):  
Amel Ennaceur ◽  
Zied Elouedi ◽  
Eric Lefèvre
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Belief Function ◽  
Multi Criteria Decision Making ◽  
Preference Assessments ◽  
Preference Relations ◽  
Expert Opinions ◽  
Expert Assessments ◽  
Mcdm Method ◽  
Modeling Expert

In modeling Multi-Criteria Decision Making (MCDM) problem, we usually assume that the decision maker is able to elicitate his preferences with precision and without difficulty. However, in many situations, the expert is unable to provide his assessment with certainty or he is unwilling to quantify his preferences. To deal with such situations, a new MCDM model under uncertainty is introduced. In fact, we focus here on the problem of modeling expert opinions despite the presence of incompleteness and uncertainty in their preference assessments. Besides, our proposed solution suggests to model these preferences qualitatively rather than exact numbers. Therefore, we propose to incorporate belief preference relations into a MCDM method. The expert assessments are then formulated as a belief function problem since this theory is considered as a useful tool to model expert judgments.

A fuzzy-logic tool for multi-criteria decision making in fisheries: the case of the South African pelagic fishery

2007 ◽  
Vol 58 (11) ◽  
pp. 1056 ◽  
Author(s):  
B. Paterson ◽  
A. Jarre ◽  
C. L. Moloney ◽  
T. P. Fairweather ◽  
C. D. van der Lingen ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
South African ◽  
Expert Opinion ◽  
Expert Knowledge ◽  
System Structure ◽  
Prototype Model ◽  
Multi Criteria Decision Making ◽  
The South ◽  
Support Tool

The present study presents an electronic decision-support tool that uses a fuzzy-logic model of expert knowledge to assist in multi-criteria decision-making in the context of an Ecosystem Approach to Fisheries (EAF). The prototype model integrates the multiple goals and objectives related to the evaluation of the ecosystem performance of the South African sardine Sardinops sagax fishery into a NetWeaver knowledge base and provides intuitive visual outputs to communicate results to managers and stakeholders. The software tool was developed in a consultative process with key experts and follows the hierarchical tree approach recommended in the FAO guidelines for responsible fisheries. Input variables are based both on quantitative data and expert opinion. We evaluated the model in terms of robustness to input changes, influence of system structure, and appropriateness of input scales for parameters based on expert opinion. Results show that the model is robust and conservative. The strength of the approach lies in the ability to include variables that are difficult to measure. It provides a means of rendering value judgements explicit and transparent. The tool synthesises a large amount of information and aims at improving understanding rather than achieving precision. The system has the potential to have wide application in the context of EAF.

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