Artificial Intelligence in Stochastic Multiple Criteria Decision Making

2017 ◽  
pp. 315-340
Author(s):  
Hanna Sawicka
Keyword(s):  
Decision Making ◽  
Probability Theory ◽  
Distribution System ◽  
Multiple Criteria Decision Making ◽  
Pharmaceutical Products ◽  
Multiple Criteria ◽  
Distribution Centers ◽  
Promethee Ii ◽  
The Core ◽  
Mcdm Method

This chapter presents the concept of stochastic multiple criteria decision making (MCDM) method to solve complex ranking decision problems. This approach is composed of three main areas of research, i.e. classical MCDM, probability theory and classification method. The most important steps of the idea are characterized and specific features of the applied methods are briefly presented. The application of Electre III combined with probability theory, and Promethee II combined with Bayes classifier are described in details. Two case studies of stochastic multiple criteria decision making are presented. The first one shows the distribution system of electrotechnical products, composed of 24 distribution centers (DC), while the core business of the second one is the production and warehousing of pharmaceutical products. Based on the application of presented stochastic MCDM method, different ways of improvements of these complex systems are proposed and the final i.e. the best paths of changes are recommended.

Artificial Intelligence in Stochastic Multiple-Criteria Decision Making

2020 ◽  
pp. 957-982
Author(s):  
Hanna Sawicka
Keyword(s):  
Decision Making ◽  
Probability Theory ◽  
Distribution System ◽  
Multiple Criteria Decision Making ◽  
Pharmaceutical Products ◽  
Multiple Criteria ◽  
Distribution Centers ◽  
Promethee Ii ◽  
The Core ◽  
Mcdm Method

This chapter presents the concept of stochastic multiple criteria decision making (MCDM) method to solve complex ranking decision problems. This approach is composed of three main areas of research, i.e. classical MCDM, probability theory and classification method. The most important steps of the idea are characterized and specific features of the applied methods are briefly presented. The application of Electre III combined with probability theory, and Promethee II combined with Bayes classifier are described in details. Two case studies of stochastic multiple criteria decision making are presented. The first one shows the distribution system of electrotechnical products, composed of 24 distribution centers (DC), while the core business of the second one is the production and warehousing of pharmaceutical products. Based on the application of presented stochastic MCDM method, different ways of improvements of these complex systems are proposed and the final i.e. the best paths of changes are recommended.

scholarly journals The application of the multiple criteria decision making/aiding methodology to evaluation and redesign of logistics systems

2020 ◽  
Vol 13 ◽  
Author(s):  
Jacek Żak
Keyword(s):  
Decision Making ◽  
Distribution System ◽  
Decision Problem ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Mathematical Programming Problem ◽  
Distribution Centers ◽  
Logistics Systems ◽  
First Case

The paper presents the methodological background of Multiple Criteria Decision Making/Aiding (MCDM/A) and its practical application in logistics systems. It explains why MCDM/A methodology is important while dealing with different categories of decision problems that arise in those systems. Major features and basic notions of MCDM/A methodology are presented. Different categories of MCDM/A methods are characterized and classified. Two case studies demonstrate possible applications of MCDM/A methodology in logistics. In the first case study multiple objective optimization of the distribution system is carried out and compared with the single objective optimization. The decision problem is formulated as multiple criteria mathematical programming problem and solved by an extended version of MS Excel Solver – Premium Solver Plus. The second case study focuses on the multiple criteria evaluation and ranking of the logistics infrastructure objects, i.e. a set of warehouses – distribution centers. The decision problem is formulated as a multiple criteria ranking problem and solved with an application of ELECTRE III/IV method.

scholarly journals The Art of Supporting Decision-Making

2017 ◽  
Vol 4 (2) ◽  
pp. 298-308 ◽  
Author(s):  
Marco Cinelli ◽  
Marco Cinelli
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Success Factors ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Comprehensive Understanding ◽  
The Core ◽  
Decision Making Processes ◽  
Support Methods ◽  
Research Domains

The provision of decision support methods and strategies is of primary importance to guarantee justifiable decision-making processes. Many of the experts and practitioners in this area gathered from 3 to 7 August 2015 at the 23rd Conference of the International Society on Multiple Criteria Decision Making at Helmut-Schmidt University in Germany. This critical reflection gathers the opinions and perspectives of eight leading scholars in the area of decision support, which were mostly video-recorded at this conference. The core findings of those interviews are summarized in this article, which focuses on (i) what Multiple Criteria Decision Making, Analysis and Aiding (MCDM/A) is, (ii) its main strengths and success factors, (iii) the recommended pathway to pursue a comprehensive understanding of MCDM/A; (iv) the main areas of application where MCDM/A is used; and (v) the recommended approaches to integrate MCDM/A in other research domains.

scholarly journals Multiple Criteria Decision Making and Prospective Scenarios Model for Selection of Companies to Be Incubated

Algorithms ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 111
Author(s):  
Altina S. Oliveira ◽  
Carlos F. S. Gomes ◽  
Camilla T. Clarkson ◽  
Adriana M. Sanseverino ◽  
Mara R. S. Barcelos ◽  
...  
Keyword(s):  
Decision Making ◽  
Evaluation Model ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Mcdm Method ◽  
Selection Of

This paper proposes a model to evaluate business projects to get into an incubator, allowing to rank them in order of selection priority. The model combines the Momentum method to build prospective scenarios and the AHP-TOPSIS-2N Multiple Criteria Decision Making (MCDM) method to rank the alternatives. Six business projects were evaluated to be incubated. The Momentum method made it possible for us to create an initial core of criteria for the evaluation of incubation projects. The AHP-TOPSIS-2N method supported the decision to choose the company to be incubated by ranking the alternatives in order of relevance. Our evaluation model has improved the existing models used by incubators. This model can be used and/or adapted by any incubator to evaluate the business projects to be incubated. The set of criteria for the evaluation of incubation projects is original and the use of prospective scenarios with an MCDM method to evaluate companies to be incubated does not exist in the literature.

Using a fuzzy multiple criteria decision-making method to evaluate personal diversity perception to work in a diverse workgroup

2021 ◽  
pp. 1-22
Author(s):  
Huyen Trang Nguyen ◽  
Ta-Chung Chu
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Ranking Method ◽  
Numerical Comparison ◽  
Team Collaboration ◽  
The Mean ◽  
Mcdm Method ◽  
Fuzzy Mcdm

Understanding employees’ perceptions in team collaboration may help managers select and develop effective teamwork and efficient job completion. Numerous criteria, including qualitative and quantitative, and their importance weights must be considered in evaluating individual diversity perception; therefore, evaluating individual diversity perception is a fuzzy multiple criteria decision-making (MCDM) problem. The purpose of this paper is to use a fuzzy MCDM method to evaluate the personal perception of working in a diverse workgroup. A ranking method using the mean of relative values is proposed to rank the final fuzzy values to complete the model. Formulas of the ranking procedure are derived to help execute the decision-making procedure and a numerical comparison is conducted to demonstrate the advantage of the proposed ranking method. In addition, a survey about personal diversity perception and willingness to work verifies the feasibility and validity of the proposed mean of relative values based fuzzy MCDM method. The results indicate that decision-makers prefer to work in a different countries-same working field group. More experienced decision-makers, unlike students, prefer to work in the same working sector group.

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