Implementing a Cloud-Based Decision Support System in a Private Cloud

2016 ◽  
Vol 8 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Imene Benatia ◽  
Mohamed Ridda Laouar ◽  
Hakim Bendjenna ◽  
Sean B. Eom
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Processing Time ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Promethee Ii ◽  
Urban Project ◽  
The Cost

This paper introduces the architecture and the deployment of a Cloud based decision support system (DSS). The DSS the authors proposed is deployed on a platform Cloud (CloudBees) and managed by the OpenStack infrastructure. The DSS is built on the Cloud Computing architecture with three layers and includes the multiple criteria decision making (MCDM) method PROMETHEE II as well as the procedure of negotiation Hare in order to help the decision makers to select the best urban project. The Cloud based DSS reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility and decrease the cost. The Cloud based multiple criteria DSS the authors designed and implemented has significant advantages. It reduces the deployment and processing time, ameliorates the communication and the cooperation between the decision makers, facilitates the accessibility, and decrease the cost.

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.

A MULTIPLE CRITERIA ENERGY DECISION SUPPORT SYSTEM / ENERGETIKOS DAUGIAKRITERINĖ SPRENDIMŲ PARAMOS SISTEMA

2011 ◽  
Vol 17 (2) ◽  
pp. 219-245 ◽  
Author(s):  
Kazim Baris Atici ◽  
Aydin Ulucan
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Energy Sector ◽  
Multiple Criteria ◽  
Decision Makers ◽  
Decision Problems ◽  
Electricity Distribution ◽  
Energy And Environment ◽  
Selection Of

Multiple Criteria Decision Analysis (MCDA) techniques are particularly suitable for Energy and Environment (E&E) decisions due to multiple criteria nature of these types of problems and they have been widely applied in this area. Main points that can be taken into consideration when examining the MCDA literature related to E&E are the selection of appropriate method, selection of criteria to be used and the widely distributed application areas. The motivation behind this study is designing such a Decision Support System (DSS) that enables the energy decision makers to perform analysis using different methods of MCDA and different criteria from various application areas and test the applicability of the system through an application in Turkish Energy Sector. The system includes several methods of MCDA and common parameters from previous studies in order to provide different approaches of evaluating decision problems. With this feature, the system stands on the intersection of MCDA and E&E fields. Moreover, an application of MCDA in Turkish Energy Sector has been performed to test the applicability of the system and some conclusions about electricity distribution in Turkey are put forth. Santrauka Daugiakriterinės sprendimų analizės (DKSA) metodai yra ypač tinkami energetikos ir aplinkos (E ir A) sprendimams priimti dėl daugiakriterinio problemų pobūdžio ir šioje srityje metodai buvo plačiai naudojami. Svarbiausi punktai, į kuriuos gali būti atsižvelgta nagrinėjant DKSA literatūrą, susijusą su E ir A, yra tinkamo metodo parinkimas, galimų rodiklių parinkimas ir plačiai paplitusios taikymo sritys. Šio mokslinio straipsnio motyvas yra suformuoti tokias sprendimų paramos sistemas (SPS), kurios leidžia energetikos sprendimus priimantiems asmenims atlikti analizę naudojant įvairius DKSA metodus ir skirtingus rodiklius iš įvairių taikymo sričių bei bandyti pritaikyti šią sistemą remiantis Turkijos energetikos sektoriumi. Sistema apima kelis DKSA metodus ir bendrus parametrus, iš ankstesnių mokslinių straipsnių, siekiant užtikrinti skirtingų požiūrių buvimą vertinant sprendimų priėmimo problemas. Šiame straipsnyje sprendimų sistema yra sankirtoje tarp DKSA bei E ir A. Be to, buvo atliktas DKSA pritaikymas Turkijos energetikos sektoriuje siekiant patikrinti sistemos pritaikomumą bei yra pateikti keli pasiūlymai dėl elektros paskirstymo Turkijoje.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU PRODUKTIF PESERTA PELATIHAN ASESOR KOMPETENSI LSP P1 SMK SWASTA DWIWARNA MEDAN MENGGUNAKAN METODE THE EXTENDED PROMETHEE II (EXPROM II)

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Dwika Assrani ◽  
Mesran Mesran ◽  
Ronda Deli Sianturi ◽  
Yuhandri Yuhandri ◽  
Akbar Iskandar
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multicriteria Analysis ◽  
Professional Certification ◽  
Promethee Ii ◽  
Certification Exams ◽  
The Government ◽  
Alternative Ranking ◽  
The Right

Vocational schools that have been licensed from BNSP to LSP P1 (first party professional certification institute) are schools that have been able to carry out their own competency certification exams for their students and later a competency assessor who will test and declare the eligibility of the students, competency assessors are productive teachers who have participated in and been given training by the government, in that training the schools choose from the number of productive teachers from each department to become competency assessor trainees in accordance with predetermined criteria so a decision support system is needed so there is no gap in the selection of productive teacher assessor training participants, a vocational school that has become a P1 LSP must have a competency assessor and is a requirement to be a P1 LSP. one of the solutions to the problem is the right one by using the Decision Support System (SPK). Decision Support System (DSS) can help the school in making the decision to choose the productive teacher of the appropriate assessor training and improve the efficiency of the decision. The Extended Promethee II (EXPROM II) is a development of the Promethee II method based on the ideal and anti-ideal solution. Promethee II itself is a method of making decisions on the function of preferences with problems through an outranking approach (ranking) or is a multicriteria analysis, comparing one alternative to another and calculating the alternative gap in pairs so as to produce an output that is alternative ranking based on the highest value.Keywords: Competitive Assessor LSP P1, SPK, The Extended Promethee II

scholarly journals A Decision Support System for Public Funding of Experimental Development in Energy Research

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1357 ◽  
Author(s):  
Simon Hirzel ◽  
Tim Hettesheimer ◽  
Peter Viebahn ◽  
Manfred Fischedick
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Public Funding ◽  
Evaluation Process ◽  
Decision Makers ◽  
Market Failures ◽  
Energy Research ◽  
Experimental Development

New energy technologies may fail to make the transition to the market once research funding has ended due to a lack of private engagement to conclude their development. Extending public funding to cover such experimental developments could be one way to improve this transition. However, identifying promising research and development (R&D) proposals for this purpose is a difficult task for the following reasons: Close-to-market implementations regularly require substantial resources while public budgets are limited; the allocation of public funds needs to be fair, open, and documented; the evaluation is complex and subject to public sector regulations for public engagement in R&D funding. This calls for a rigorous evaluation process. This paper proposes an operational three-staged decision support system (DSS) to assist decision-makers in public funding institutions in the ex-ante evaluation of R&D proposals for large-scale close-to-market projects in energy research. The system was developed based on a review of literature and related approaches from practice combined with a series of workshops with practitioners from German public funding institutions. The results confirm that the decision-making process is a complex one that is not limited to simply scoring R&D proposals. Decision-makers also have to deal with various additional issues such as determining the state of technological development, verifying market failures or considering existing funding portfolios. The DSS that is suggested in this paper is unique in the sense that it goes beyond mere multi-criteria aggregation procedures and addresses these issues as well to help guide decision-makers in public institutions through the evaluation process.

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