scholarly journals A Decision Support System for Solving Multiple Criteria Optimization Problems

2011 ◽  
Vol 10 (2) ◽  
pp. 213-224 ◽  
Author(s):  
Ernestas FILATOVAS ◽  
Olga KURASOVA
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Optimization Problems ◽  
Multiple Criteria ◽  
Multiple Criteria Optimization

scholarly journals Teknik Pengambilan Keputusan Multi Kriteria Menggunakan Metode BAYES, MPE, CPI dan AHP

2011 ◽  
Vol 2 (1) ◽  
pp. 229
Author(s):  
Abdul Haris Rangkuti
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multiple Criteria ◽  
Complex Dynamic ◽  
Bayes Method ◽  
Application Program ◽  
Structured Problems

Decision making at every company is something very important and vital. Decision making can be influenced by several aspects, so it can affect the promptness and accuracy of the process, especially when solving any complex, dynamic and less structured problems. Therefore, the combination of multiple criteria concept and an application program of decision-support system is an effective way to generate alternative decisions. The methods used for multiple criteria are: Bayes method, MPE, CPI and the AHP. This article discusses the use of each method, adapted to each problem. The four methods happen to be very effective with the help of the application program of decision support system. Expectantly these methods are able to assist company managements in decision-making. 

scholarly journals AN IDIOSYNCRATIC DECISION SUPPORT SYSTEM FOR CREDIT RISK ANALYSIS OF SMALL AND MEDIUM-SIZED ENTERPRISES

2015 ◽  
Vol 22 (4) ◽  
pp. 598-616 ◽  
Author(s):  
Tânia S. H. GONÇALVES ◽  
Fernando A. F. FERREIRA ◽  
Marjan S. JALALI ◽  
Ieva MEIDUTĖ-KAVALIAUSKIENĖ
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Credit Risk ◽  
Support System ◽  
Cognitive Mapping ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Trade Offs ◽  
Credit Risk Analysis ◽  
Mapping Techniques

Small and medium-sized enterprises (SMEs) are currently considered an important driving force of economic growth. Several studies have been developed to analyse this issue and, in particular, to assess the credit risk of SMEs. Most of these applications, however, share the same methodological limitations, such as the manner by which criteria are selected, or the methods used for calculating the weights between them. Based on the integrated use of cognitive mapping techniques and the Interactive Multiple Criteria Decision Making (TODIM) approach, this study aims to create an idiosyncratic decision support system for the identification of multiple criteria and the calculation of their respective weights (i.e. the trade-offs) in the evaluation of SME credit risk. The results show that the model created in this study allows for simple and straightforward credit concession decisions, facilitating the evaluation of SME credit applications through more informed and transparent risk assessments. Practical implications, strengths and weaknesses of the proposed framework are analysed and discussed.

Development of Neural-Net-Based Decision Support System for Mattress Patterns Using Particle Swarm Optimization

2010 ◽  
Vol 4 (2) ◽  
pp. 178-183 ◽  
Author(s):  
Mitsue Kato ◽  
◽  
Toru Yamamoto ◽  
Keyword(s):  
Particle Swarm Optimization ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Optimization Problems ◽  
Learning Algorithm ◽  
Particle Swarm ◽  
Neural Net ◽  
Swarm Optimization ◽  
Neural Network Learning

The particle swarm optimization (PSO) concept simulating a simplified social milieu, is optimization useful for solving nonconvex continuous optimization problems. We discuss a new learning algorithm for simultaneously adjusting connection weights in neural networks and user-specified parameters included in units. Based on our algorithm, neural network learning, e.g., learning cost or adaptability, can be improved, as demonstrated in mattress decision support system.

MULTIPLE CRITERIA DECISION SUPPORT SYSTEM FOR ASSESSMENT OF PROJECTS MANAGERS IN CONSTRUCTION

2012 ◽  
Vol 11 (02) ◽  
pp. 501-520 ◽  
Author(s):  
EDMUNDAS KAZIMIERAS ZAVADSKAS ◽  
POVILAS VAINIŪNAS ◽  
ZENONAS TURSKIS ◽  
JOLANTA TAMOŠAITIENĖ
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Construction Projects ◽  
Assessment Method ◽  
Project Managers ◽  
Multiple Criteria ◽  
Expert Judgement ◽  
Effective Management ◽  
Decision Aiding

Construction processes planning and effective management are extremely important for success in construction business. Head of a design must be well experienced in initiating, planning, and executing of construction projects. Therefore, proper assessment of design projects' managers is a vital part of construction process. The paper deals with an effective methodology that might serve as a decision support aid in assessing project managers. Project managers' different characteristics are considered to be more or less important for the effective management of the project. Qualifying of managers is based on laws in force and sustainability of project management involving determination of attributes value and weights by applying analytic hierarchy process (AHP) and expert judgement methods. For managers' assessment and decision supporting is used additive ratio assessment method (ARAS). The model, presented in this study, shows that the three different methods combined (ARAS method aggregated together with the AHP method and the expert judgement method) is an effective tool for multiple criteria decision aiding. As a tool for the assessment of the developed model, was developed multiple criteria decision support system (MCDSS) weighting and assessment of ratios (WEAR) software. The solution results show that the created model, selected methods and MCDSS WEAR can be applied in practice as an effective decision aid.

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