819 resultados para Decision systems
Resumo:
The reasons of a restricted applicability of the models of decision making in social and economic systems. 3 basic principles of growth of their adequacy are proposed: "localization" of solutions, direct account of influencing of the individual on process of decision making ("subjectivity of objectivity") and reduction of influencing of the individual psychosomatic characteristics of the subject (" objectivity of subjectivity ") are offered. The principles are illustrated on mathematical models of decision making in ecologically- economic and social systems.
Resumo:
Methods of analogous reasoning and case-based reasoning for intelligent decision support systems are considered. Special attention is drawn to methods based on a structural analogy that take the context into account. This work was supported by RFBR (projects 02-07-90042, 05-07-90232).
Resumo:
The question of forming aim-oriented description of an object domain of decision support process is outlined. Two main problems of an estimation and evaluation of data and knowledge uncertainty in decision support systems – straight and reverse, are formulated. Three conditions being the formalized criteria of aimoriented constructing of input, internal and output spaces of some decision support system are proposed. Definitions of appeared and hidden data uncertainties on some measuring scale are given.
Resumo:
Development of methods and tools for modeling human reasoning (common sense reasoning) by analogy in intelligent decision support systems is considered. Special attention is drawn to modeling reasoning by structural analogy taking the context into account. The possibility of estimating the obtained analogies taking into account the context is studied. This work was supported by RFBR.
Resumo:
Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.
Resumo:
Industry practitioners are seeking to create optimal logistics networks through more efficient decision-making leading to a shift of power from a centralized position to a more decentralized approach. This has led to researchers, exploring with vigor, the application of agent based modeling (ABM) in supply chains and more recently, its impact on decision-making. This paper investigates reasons for the shift to decentralized decision-making and the impact on supply chains. Effective decentralization of decision-making with ABM and hybrid modeling is investigated, observing the methods and potential of achieving optimality.
Resumo:
A „Vezetési és döntési rendszerek” alprojekt kutatói a döntéshozatal minőségének és a versenyképességnek a kapcsolatát vizsgálták. Alapkérdésünk az volt, hogy mely vállalatok a sikeresebbek, azok, amelyek a döntéshozatali közelítésmódok közül a szigorúan racionális, analitikus gondolkodást, felfogást favorizálják, vagy inkább a kreativitást ösztönző és középpontba állító, a kreatív döntéshozatali és vezetési stílust követő cégek. Azt tapasztaltuk, hogy a vállalatok menedzsmentjének egyre többször kell megbirkóznia vészhelyzetekkel és azok következményeivel. Az üzleti döntések és az üzleti teljesítmény, az üzleti siker kapcsolatának vizsgálatára külön kutatási irányt jelöltünk meg. A felelős döntéshozatal témakörében a mi kutatásunk a konkrét döntéseket helyezte előtérbe, amely új közelítésmódot jelent. Ugyanis nem csak specifikus CSR gyakorlatokkal foglalkoztunk, hanem konkrét vezetői döntésekben vizsgáltuk meg a CSR és a fenntarthatóság elemeit. ______ Within the framework of the “Management and decision-making systems” subproject we investigated the link between the quality of decision making and competitiveness. Our basic question was the following: which companies are more successful, those who are strictly follow the rational/analytical way of decision making or the others who mainly focus on creative decision making and creative management. We found that nowadays the company managements more often face to crisis situations and their consequences. We initiated a focused research on the relationship of the business decision making, business performance and business success. When we did research in the field of the responsible decision making we focused on concrete decision cases, that was a brand new approach. We have not analyzed the CSR practice, but identified CSR and sustainability elements in concrete management decisions.
Resumo:
Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, non-integrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. ^ A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. ^ One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects. ^
Resumo:
Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.
Resumo:
Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence technique inspired by immunology has emerged, called Artificial Immune Systems (AIS). This immune system inspired technique has already been useful in solving some computational problems. In this keynote, we will very briefly describe the immune system metaphors that are relevant to AIS. We will then give some illustrative real-world problems suitable for AIS use and show a step-by-step algorithm walkthrough. A comparison of AIS to other well-known algorithms and areas for future work will round this keynote off. It should be noted that as AIS is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from the examples given here
Resumo:
In some Queensland universities, Information Systems academics have moved out of Business Faculties. This study uses a pilot SWOT analysis to examine the ramifications of Information Systems academics being located within or outside of the Business Faculty. The analysis provides a useful basis for decision makers in the School studied, to exploit opportunities and minimise external threats. For Information Systems academics contemplating administrative relocation of their group, the study also offers useful insights. The study presages a series of further SWOT analyses to provide a range of perspectives on the relative merits of having Information Systems academics administratively located inside versus outside Business faculties.