Higher education decision making and decision support systems

The authors illustrate several issues in decision support and decision support systems (DSS), state of the art research in these fields, and also their own studies in designing a higher education DSS. The final section contains our contribution in outlining the modules of the DSS, involving the present systems and databases of FSEGA and UBB, results and activities belonging to FSEGA students, teaching and research staff, to assist decisions for all the actors implicated in the processes, in various specific situations.decision support, decision support systems (DSS), higher education institutions, Information and Communication Technologies (ICT)

Combining Fuzzy AHP with GIS and Decision Rules for Industrial Site Selection

This study combines Fuzzy Analytic Hierarchy Process (FAHP), Geographic Information System (GIS) and Decision rules to provide decision makers with a ranking model for industrial sites in Algeria. A ranking of the suitable industrial areas is a crucial multi-criteria decision problem based on socio-economical and technical criteria as on environmental considerations. Fuzzy AHP is used for assessment of the candidate industrial sites by combining fuzzy set theory and analytic hierarchy process (AHP). The decision rule base serves as a filter that performs criteria pre-treatment involving a reduction of their numbers. GIS is used to overlay, generate criteria maps and for visualizing ranked zones on the map. The rank of a zone so obtained is an index that guides decision-makers to the best utilization of the zone in future

Информационные системы для автомобильных перевозок

The article considers the selection of management systems of transportation activities. A review of IT-solutions for the transport and logistics business, existing in the Russian market, is given and an approach is offered justifying the assessment of functional and non-functional characteristics of the system being implemented. It is based on modern methods, which help to select software, which is suitable for targets.В статье рассматривается процесс выбора систем управления перевозочной деятельностью. Дается обзор существующих на российском рынке IT-решений для транспортно-логистического бизнеса и предлагается подход, обосновывающий оценку функциональных и нефункциональных  характеристик внедряемой системы. Он опирается на современные методики, которые помогают выбрать адекватное целям программное обеспечение

Decision support system for building information modeling (BIM) software selection: A case study in construction feasibility stage

The adoption of Building Information Modelling (BIM) software has proven to be beneficial to the construction industry to improve the design, analysis, construction, operation and data management. Due to the variety of BIM software on the market, choosing the right BIM software in construction projects is deemed to be a complicated decision making process. Previous studies revealed that software selection is mainly made based on popularity and recommendation from other companies. Consequently, inaccurate selection would lead to the underutilised features and negative effect the investment on the BIM software. Based on literature, there is a lack of systematic approach to select the right BIM software for specific project requirements. This highlights the needs for decision making tools to select the appropriate BIM software. This research aims to develop a Decision Support System (DSS) named topsis4BIM which integrates graphical user interfaces, BIM features database, Fuzzy TOPSIS and Web 2.0 tools. A real construction project was used as a case study for demonstrating and validating the DSS framework. The findings indicate that the use of topsis4BIM improves the BIM software selection process compared to the current practice. In addition, it also produce a new framework for the next generation DSS using Web 2.0 tools. The study introduces an innovative and economical decision making approach that can guide construction practitioners towards the betterment of BIM adoption

Risk-based decision support system for life cycle management of industrials plants

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de ComputadoresThe objective of this thesis is to contribute for a better understanding of the decision making process in industrial plants specifically in situations with impact in the long term performance of the plant. The way decisions are made, and especially the motivations that lead to the selection of a specific course of action, are sometimes unclear and lack on justification. This is particularly critical in cases where inappropriate decisions drive to an increase on the production costs. Industrial plants are part of these cases, specifically the ones that are still lacking enhanced monitoring technologies and associated decision support systems. Maintenance has been identified as one of the critical areas regarding impact on performance. This is due to the fact that maintenance costs still represent a considerable slice of the production costs. Thus, understanding the way maintenance procedures are executed, and more important, the methods used to decide when maintenance should be developed and how, have been a concern of decision makers in industrial plants. This thesis proposes a methodology to efficiently transform the existing information on the plant behaviour into knowledge that may be used to support the decision process in maintenance activities. The development of an appropriate knowledge model relating the core aspects of the process enables the extraction of new knowledge based on the past experience. This thesis proposes also a methodology to calculate the risk associated to each maintenance situation and, based on the possible actions and on the impacts they may have in the plant costs performance, suggests the most appropriate course. The suggestion is made aiming the minimization of the life cycle costs. Results have been validated in test cases performed both at simulation and real industrial environments. The results obtained at the tests cases demonstrated the feasibility of the developed methodology as well as its adequateness and applicability in the domain of interest

A practical framework for assessing business intelligence competencies of enterprise systems using fuzzy ANP approach

As traditional concept in management, decision support had a remarkable role in competitiveness or survival of organisations and following, as modern impression, nowadays business intelligence (BI) has various applications in achieving desirable decision supports. Consequently, assessing BI competencies of enterprise systems can enable decision support in firms. This paper presents a practical framework for assessing the business intelligence capabilities of enterprise systems based on a set of novel factors and utilising fuzzy analytic network process (FANP). Through this, the construct of BI competency is decomposed into three main competency parts including ‘managerial’, ‘technical’ and ‘system enabler’ sub-goals, five main factors and 26 criteria. Using this framework, the BI competency level of enterprise systems can be determined which can help the decision makers to select the enterprise system that best suits organisations’ intelligence decision support needs. In order to validate the proposed model, it is applied to a real Iranian international offshore engineering and construction company in the oil industry to select and acquire ERP system. This research provides a complete frame (factors, criteria and procedures) for firms to assess their proposed software and systems in the field of BI competencies and functions