Proefschrift Universiteit van Tilburg. / Met lit. opg. - Met samenvatting in het Nederlands.

Proefschrift Erasmus Universiteit Rotterdam.

Proefschrift Erasmus Universiteit Rotterdam.

Proefschrift Maastricht. / Auteursnaam op omslag: Frits van Merode. Met lit. opg. - Met samenvatting in het Nederlands.

M.Com. (Business Management) / The ultimate objective of this research report was to develop a Decision Support System, (DSS), that can be used by property professionals to enable them to make better decisions regarding property development in South Africa. The DSS addresses the problem of numerous uncertain variables in property development investment decisions. The capability of the computer to do repetitive calculations with different combinations of variables, with probabilities linked to each variable, was used in a Monte Carlo analysis. The DSS was developed on a "Lotus 1-2-3™ Release 4 for Windows" spreadsheet which makes the program adaptable to suit specific applications if the need arises. The DSSwill, however, be able to address the majority of property developments without any adaptation. The DSS was appraised by property professionals and the comments received from the respondents indicate that the primary objective stated was achieved. The DSS is best suited for property investors who are also involved in the early development phases.

When non-recurrent road traffic congestion happens, the operator of the traffic control centre has to select the most appropriate traffic control measure or combination of measures in a short time to manage the traffic network. This is a complex task, which requires expert knowledge, much experience and fast reaction. There are a large number of factors related to a traffic state as well as a large number of possible control measures that need to be considered during the decision making process. The identification of suitable control measures for a given non-recurrent traffic congestion can be tough even for experienced operators. Therefore, simulation models are used in many cases. However, simulating different traffic scenarios for a number of control measures in a complicated situation is very time-consuming. In this paper we propose an intelligent traffic control decision support system (ITC-DSS) to assist the human operator of the traffic control centre to manage online the current traffic state. The proposed system combines three soft-computing approaches, namely fuzzy logic, neural network, and genetic algorithm. These approaches form a fuzzy-neural network tool with self-organization algorithm for initializing the membership functions, a GA algorithm for identifying fuzzy rules, and the back-propagation neural network algorithm for fine tuning the system parameters. The proposed system has been tested for a case-study of a small section of the ring-road around Riyadh city. The results obtained for the case study are promising and show that the proposed approach can provide an effective support for online traffic control.

The objectives of this research are threefold: (i) to develop a conceptual framework and a prototype in order to extend the application capability of a category of multiple objective decision support systems (MODSS) techniques; (ii) to explore the combined functionalities of knowledge-based expert systems (ES) and MODSS through embedding an intelligent front-end, and (iii) to develop a new system and process of dealing with multiple objective decision making (MODM) models in a group decision support system (GDSS) framework. Ultimately, a system that integrates MODSS, ES and GDSS is generated, which is then evaluated in a laboratory experimental setup. This integrated system contains a sufficient number of MODM methods to solve MODM problems, provides an ES-based guide to select and use the most suitable MODM method, and has the capability to aggregate individual decision makers' preferences to produce a compromise solution of an MODM problem in different forms and styles of group meetings. The system is supported by a set of group decision making (GDM) methods which combine the preferences of the individual group members and thus increases the confidence of each group member in the compromise solution.The research is conducted using a multiple-methodologies approach using the system development methodology as the backbone. The conceptual framework of the integrated system is elaborated to integrate multiple system elements into one facility at the application system level based on functional and resource integration. A prototype implements this conceptual framework as an intelligence-based and graphical user interface (GUI)-based MODSS that works in an individual/group environment. Both the conceptual framework and the prototype are called Intelligent Multiple Objectives Group Decision Support Systems (IMOGDSS).Initial evaluation of the IMOGDSS is encouraging, which ++ / is conducted in the form of testing a number of hypotheses in an experimental setup. This research thus makes contributions in both theoretical and application domains. Five major contributions are listed below:It develops a unique conceptual framework of integrating MODSS, ES and GDSS effectively to deal with MODM problem in individual/group decision making under a knowledge-based intelligent architecture.It provides a new application of ES, that is, utilising knowledge-based ES to select the most efficient MODM method for each particular decision maker (or decision group) in a particular decision problem.The complete method management function of the MODM methodology base guides the decision makers to use the most suitable method to solve their decision making problems, allows them to use multiple methods to resolve complex problems, that could not otherwise be solved with a single MODM, and also allows the group members to get solutions from different methods.This study produces an opportunity to select and apply the 'best' aggregation model to aggregate the individual solutions of an MODM problem through integrating various GDM methods in a methodology base.This study implements a two-stage configuration of group decision support software that provides a GUI-based hierarchical procedure for solving MODM problems with intelligent guidance in a decision group. The two-stage group decision making procedure is able to help the decision makers to analyse, understand and interact cooperatively in the group decision making process to reach a compromise solution.

Thesis (Ph. D.)--University of Missouri--Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 104-114).

Thesis (doctoral)--Rijksuniversiteit Groningen, 1992. / Includes bibliographical references (p. 223-230).

Thesis (M.H.A.)--University of Michigan, 1975.