scholarly journals CONCEPTUAL DECISION MODEL

2014 ◽  
pp. 69-73
Author(s):  
Miki Sirola
Keyword(s):  
Decision Making ◽  
Decision Problem ◽  
Decision Model ◽  
Numerical Algorithms ◽  
Fine Tuning ◽  
Computer Application ◽  
Decision Table ◽  
Case Examples ◽  
Numerical Result ◽  
Decision Attributes

Decision making is mostly based on decision concepts and decision models built in decision support systems. Type of decision problem determines application. This paper presents a conceptual decision model that utilises rule- based methodologies, numerical algorithms and procedures, statistical methodologies including distributions, and visual support. Selection of used decision concepts is based on case-based needs. Fine tuning of the model is done during construction of the computer application and analysis of the case examples. A kind of decision table is built including pre-filtered decision options and carefully chosen decision attributes. Each attribute is weighted, decision table values are given, and finally total score is calculated. This is done with a many-step procedure including various elements. The computer application is built on G2 platform. The case example choice of career is analysed in detail. The developed prototype should be considered mostly as an advisory tool in decision making. More important than the numerical result of the analysis is to learn about the decision problem. Evaluation expertise is needed in the development process. The model constructed is a kind of completed multi-criteria decision analysis concept. This paper is also an example of using a theoretical methodology in solving a practical problem.

AN EXTENDED BRANCH AND BOUND ALGORITHM FOR BILEVEL MULTI-FOLLOWER DECISION MAKING IN A REFERENTIAL-UNCOOPERATIVE SITUATION

2007 ◽  
Vol 06 (02) ◽  
pp. 371-388 ◽  
Author(s):  
JIE LU ◽  
CHENGGEN SHI ◽  
GUANGQUAN ZHANG ◽  
DA RUAN
Keyword(s):  
Decision Making ◽  
Branch And Bound ◽  
Decision Problem ◽  
Decision Model ◽  
Branch And Bound Algorithm ◽  
Upper Level ◽  
Multiple Followers ◽  
Cross Reference

Within the framework of any bilevel decision problem, a leader's decision at the upper level is influenced by the reaction of their follower at the lower level. When multiple followers are involved in a bilevel decision problem, the leader's decision will not only be affected by the reactions of those followers, but also by the relationships among those followers. One of the popular situations within this framework is where these followers are uncooperatively making decisions while having cross reference of decision information, called a referential-uncooperative situation in this paper. The well-known branch and bound algorithm has been successfully applied to a one-leader-and-one-follower linear bilevel decision problem. This paper extends this algorithm to deal with the above-mentioned linear bilevel multi-follower decision problem by means of a linear referential-uncooperative bilevel multi-follower decision model. It then proposes an extended branch and bound algorithm to solve this problem with a set of illustrative examples in a referential-uncooperative situation.

A DECISION MODEL PROPOSAL IN CASE OF UNCERTAINTY: PHOTOCOPY MACHINE SELECTION WITH ENTROPY-BASED ELECTRE III METHOD

2021 ◽  
Vol 6 (11) ◽  
pp. 82-92
Author(s):  
Engin KARAKIŞ
Keyword(s):  
Decision Making ◽  
Decision Problem ◽  
Decision Model ◽  
Entropy Method ◽  
Decision Problems ◽  
Suitable Alternative ◽  
Electre Iii ◽  
Machine Selection ◽  
Technological Developments ◽  
Fast Decision

Decision making is getting more complex and difficult in our daily life and business life. However, correct and fast decision making is the first condition of managing and directing. The complexity and uncertainty in decision problems have increased as a result of technological developments and changes in consumer demands. Most of the decision problems encountered contain many criteria. Multi-Criteria Decision Making (MCDM) is to choose the most suitable alternative among many alternatives according to more than one determined criteria. Various methods have been developed for the solution of multi-criteria decision problems. ELECTRE III (ELimination Et Choice Translating REality) method, one of these methods, is one of the most widely used methods. The ELECTRE III method is a method used in the solution of decision problems involving uncertainty. In this study, the ELECTRE III method and its properties have been examined with an application. For this purpose, the problem of photocopy machine selection was examined with the ELECTRE III method in this study. The ENTROPY method was used to determine the weights of the criteria used in the decision problem and the ELECTRE III method was used to rank the copier machine options.

scholarly journals Interval Intuitionistic Fuzzy Decision Model with Abnormal Information and Its Application in Talent Selection

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xueer Ji ◽  
Lei Wang ◽  
Huifeng Xue
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Decision Model ◽  
Correction Method ◽  
Intuitionistic Fuzzy Sets ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Talent Selection ◽  
Decision Attributes ◽  
Intuitionistic Fuzzy Entropy

In some complex decision-making problems such as talent selection, experts often hesitate between multiple evaluation values during their decision making and can only give a range of information due to the fuzziness and imprecision of qualitative decision-making attributes. Interval intuitionistic fuzzy sets and their decision-making methods provide a useful tool to describe the fuzziness of decision attributes and decision experts’ hesitation. However, the abnormal information in the expert decision information has not been considered in the previous works; that is, some interval intuitionistic fuzzy numbers exceed the defined interval range. This kind of abnormal decision information often makes it difficult to obtain accurate decision results using the decision model. To avoid the abnormal information influence on decision-making results, the hesitancy degree-based interval intuitionistic fuzzy sets are employed to propose an adaptive correction method of abnormal information, which can correct the abnormal decision information without changing the decision preference of experts. The abnormal information correction method is utilized to construct a new interval intuitionistic fuzzy entropy by combining hesitancy and fuzziness. This provides a multiattribute decision-making method, including abnormal decision information. Finally, the effectiveness and superiority of the proposed method and decision-making model are evaluated using an application case study of talent selection.

Applying the Multi-Criteria Decision Making Model for Ranking Commercial Banks: The Case of Vietnam

2019 ◽  
pp. 125-133
Author(s):  
Duong Truong Thi Thuy ◽  
Anh Pham Thi Hoang
Keyword(s):  
Decision Making ◽  
Commercial Banks ◽  
Decision Model ◽  
Business Models ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Decision Making Model

Banking has always played an important role in the economy because of its effects on individuals as well as on the economy. In the process of renovation and modernization of the country, the system of commercial banks has changed dramatically. Business models and services have become more diversified. Therefore, the performance of commercial banks is always attracting the attention of managers, supervisors, banks and customers. Bank ranking can be viewed as a multi-criteria decision model. This article uses the technique for order of preference by similarity to ideal solution (TOPSIS) method to rank some commercial banks in Vietnam.

scholarly journals Assessing the Value of Demand Response in Microgrids

2021 ◽  
Vol 13 (11) ◽  
pp. 5848
Author(s):  
Isaías Gomes ◽  
Rui Melicio ◽  
Victor M. F. Mendes
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Energy Storage ◽  
Case Studies ◽  
Demand Response ◽  
Storage Systems ◽  
Computer Application ◽  
Market Prices ◽  
Proper Formulation ◽  
Operation Case

This paper presents a computer application to assist in decisions about sustainability enhancement due to the effect of shifting demand from less favorable periods to periods that are more convenient for the operation of a microgrid. Specifically, assessing how the decisions affect the economic participation of the aggregating agent of the microgrid bidding in an electricity day-ahead market. The aggregating agent must manage microturbines, wind systems, photovoltaic systems, energy storage systems, and loads, facing load uncertainty and further uncertainties due to the use of renewable sources of energy and participation in the day-ahead market. These uncertainties cannot be removed from the decision making, and, therefore, require proper formulation, and the proposed approach customizes a stochastic programming problem for this operation. Case studies show that under these uncertainties and the shifting of demand to convenient periods, there are opportunities to make decisions that lead to significant enhancements of the expected profit. These enhancements are due to better bidding in the day-ahead market and shifting energy consumption in periods of favorable market prices for exporting energy. Through the case studies it is concluded that the proposed approach is useful for the operation of a microgrid.

scholarly journals Deep Learning-Based Differentiation between Mucinous Cystic Neoplasm and Serous Cystic Neoplasm in the Pancreas Using Endoscopic Ultrasonography

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1052
Author(s):  
Leang Sim Nguon ◽  
Kangwon Seo ◽  
Jung-Hyun Lim ◽  
Tae-Jun Song ◽  
Sung-Hyun Cho ◽  
...  
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Network Model ◽  
Endoscopic Ultrasonography ◽  
Data Augmentation ◽  
Clinical Information ◽  
Training Data ◽  
Fine Tuning ◽  
Cystic Neoplasm ◽  
Cystic Neoplasms

Mucinous cystic neoplasms (MCN) and serous cystic neoplasms (SCN) account for a large portion of solitary pancreatic cystic neoplasms (PCN). In this study we implemented a convolutional neural network (CNN) model using ResNet50 to differentiate between MCN and SCN. The training data were collected retrospectively from 59 MCN and 49 SCN patients from two different hospitals. Data augmentation was used to enhance the size and quality of training datasets. Fine-tuning training approaches were utilized by adopting the pre-trained model from transfer learning while training selected layers. Testing of the network was conducted by varying the endoscopic ultrasonography (EUS) image sizes and positions to evaluate the network performance for differentiation. The proposed network model achieved up to 82.75% accuracy and a 0.88 (95% CI: 0.817–0.930) area under curve (AUC) score. The performance of the implemented deep learning networks in decision-making using only EUS images is comparable to that of traditional manual decision-making using EUS images along with supporting clinical information. Gradient-weighted class activation mapping (Grad-CAM) confirmed that the network model learned the features from the cyst region accurately. This study proves the feasibility of diagnosing MCN and SCN using a deep learning network model. Further improvement using more datasets is needed.

scholarly journals Determinant Factors in Personal Decision-Making to Adopt COVID-19 Prevention Measures in Chile

2021 ◽  
Vol 18 (15) ◽  
pp. 8131
Author(s):  
Karina Fernanda Gonzalez ◽  
Maria Teresa Bull ◽  
Sebastian Muñoz-Herrera ◽  
Luis Felipe Robledo
Keyword(s):  
Decision Making ◽  
Decision Model ◽  
Protective Action ◽  
Prevention Measures ◽  
Protective Measures ◽  
Protective Action Decision Model ◽  
Exploratory Survey ◽  
Relevant Variables ◽  
Personal Decision ◽  
Action Decision

The pandemic has challenged countries to develop stringent measures to reduce infections and keep the population healthy. However, the greatest challenge is understanding the process of adopting self-care measures by individuals in different countries. In this research, we sought to understand the behavior of individuals who take self-protective action. We selected the risk homeostasis approach to identify relevant variables associated with the risk of contagion and the Protective Action Decision Model to understand protective decision-making in the pandemic. Subsequently, we conducted an exploratory survey to identify whether the same factors, as indicated in the literature, impact Chile’s adoption of prevention measures. The variables gender, age, and trust in authority behave similarly to those found in the literature. However, socioeconomic level, education, and media do not impact the protection behaviors adopted to avoid contagion. Furthermore, the application of the Protective Action Decision Model is adequate to understand the protective measures in the case of a pandemic. Finally, women have a higher risk perception and adopt more protective measures, and in contrast, young people between 18 and 30 years of age are the least concerned about COVID-19 infection.

Research on Investment Decision-Making of the Low-Carbon Industrial Listed Company Based on the Uncertainty Set Pair Analysis

2010 ◽  
Vol 39 ◽  
pp. 568-574
Author(s):  
Jun Fei Chen ◽  
Jian Qiao Lin
Keyword(s):  
Decision Making ◽  
Decision Model ◽  
Listed Company ◽  
Investment Decision ◽  
Set Pair Analysis ◽  
Low Carbon ◽  
Development Mode ◽  
Investment Decision Making ◽  
Uncertainty Set ◽  
Pair Analysis

As a new economical development mode, “low-carbon economic” is attracting more and more attention all over the world. In this paper, associating with the development background of the low-carbon industry, we applied the uncertainty set pair analysis (SPA) into the investment decision-making of the listed company, and established the investment decision model based on the uncertainty SPA. As a case, we made investment decision analysis to 12 typical low-carbon industrial listed companies selected. The results show that it is effective and applicable, and the research is helpful for the investors conducting decision-making.

scholarly journals Multicriteria Evaluation of Urban Regeneration Processes: An Application of PROMETHEE Method in Northern Italy

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Marta Bottero ◽  
Chiara D’Alpaos ◽  
Alessandra Oppio
Keyword(s):  
Decision Making ◽  
Decision Problem ◽  
Swot Analysis ◽  
Evaluation Model ◽  
Methodological Approach ◽  
Urban Regeneration ◽  
Northern Italy ◽  
Decision Making Process ◽  
Promethee Method ◽  
Regeneration Processes

The paper illustrates the development of an evaluation model for supporting the decision-making process related to an urban regeneration intervention. In particular, the study proposes an original multi-methodological approach, which combines SWOT Analysis, Stakeholders Analysis and PROMETHEE method for the evaluation of alternative renewal strategies of an urban area in Northern Italy. The article also describes the work carried out within an experts’ panel that has been organized for validating the structuring of the decision problem and for evaluating the criteria of the model.

Sign in / Sign up

Export Citation Format

Share Document