An interactive computer game for teaching project management skills using network models is presented. The game is written in APL notation. The game is based on a discrete simulation model of the project network. The player simulates the project for a period of time and can then solicit reports, perform resource scheduling or CPM analysis, and make changes in response to the current environmental conditions. The instructor interacts with the game through the environmental modifying functions and the scheduling of exogenous events. This allows him to create a game which is tailored to a specific pedagogical situation. Descriptions of techniques used to add these options and some suggestions for them are included. / Master of Architecture

A stochastic dynamic constituent transport model was developed, capable of simulating the operation of a water distribution system containing pumps and storage tanks, and subject to random demands and contaminant inputs. Long term operation of a hypothetical small town water supply system containing one pump station and one storage tank was simulated while the system was subjected to external contaminant inputs. Repeated simulations were made under different regimes of external contamination applied to the tank, the pump station and at system nodes, and internal contamination representing biofilm effects based on assumed relationships between flow velocities and bioflim cell detachment. Seven sampling plans representing regulatory requirements and industry practice were applied during the simulation to evaluate their ability to detect the contamination under a presence/absence criterion. The simulations were able to identify contamination patterns and provide information useful in the definition of sampling plans. Time of sampling was found to be as important as location. This was true both within the monitoring period, and particularly within the diurnal cycle of demand. Spreading samples over different days within the monitoring period rather than sampling all on one day, always improved contaminant detection. Detection by plans based on fixed times and locations were very sensitive to those times and locations. There was no best plan suitable for all situations tested. The better sampling plans were those that captured the temporal and spatial contamination patterns present in the system. No consistent advantage was noted from sampling in proportion to population served or in locating sampling nodes systematically instead of randomly. The location and timing of sampling for most plans could be improved with the knowledge of actual contamination patterns and timing provided by the model. The presence of a storage tank was found to have a strong influence on hydraulic patterns and the location and timing of contamination reaching different parts of the system. / Ph. D.

This dissertation reports on an effort to design, construct, test, and adjust an expert system for making certain business decisions. A widely used approach to recurring judgmental decisions in business and other social organizations is the "rule-based decision system". This arrangement employs staff experts to propose decision choices and selections to a decisionmaker. Such decisions can be very important because of the large resources involved. Rules and values encountered in such systems are often vague and uncertain. Major questions explored by this experimental effort were: (1) could the output of such a decision system be mimicked easily by a mechanism incorporating the rules people say they use, and (2) could the imprecision endemic in such a system be represented by fuzzy set constructs. The task environment chosen for the effort was a computer-based game which required player teams to make a number of interrelated, recurring decisions in a realistic business situation. The primary purpose of this research is to determine the feasibility of using these methods in real decision systems. The expert system which resulted is a relatively complicated, feed-forward network of "simple" inferences, each with no more than one consequent and one or two antecedents. Rules elicited from an expert in the game or from published game instructions become the causal implications in these inferences. Fuzzy relations are used to represent imprecise rules and two distinctly different fuzzy set formats are employed to represent imprecise values. Once imprecision appears from the environment or rules the mechanism propagates it coherently through the inference network to the proposed decision values. The mechanism performs as well as the average human team, even though the strategy is relatively simple and the inferences crude linear approximations. Key aspects of this model, distinct from previous work, include: (1) the use of a mechanism to propose decisions in situations usually considered ill-structured; (2) the use of continuous rather than two-valued variables and functions; (3) the large scale employment of fuzzy set constructs to represent imprecision; and (4) use of feed forward network structure and simple inferences to propose human-like decisions.

This research assisted the Yuma, Arizona citrus orchard manager in his strategic planning for achieving a low-cost position in a focused segment of the citrus industry. Citrus growers in the Yuma district are faced with major changes in their competitive environment and must adopt new strategic plans in order to continue to compete effectively in what has recently become a global industry. Since the planning horizon for new citrus orchards is in excess of 20 years, a long range planning model was developed to aid in evaluating alternative operating strategies. This research established the interrelatedness of water, nitrogen, and phosphorous relative to the yields of Valenica Oranges, Lisbon Lemons, and Redblush Grapefruit on Rough Lemon, Sour Orange, and Troyer rootstocks. A computer simulation model was used to evaluate optimal operating policies for a variety of resource prices and market conditions. The methodology utilized in development of the simulation model was unique in that it emulates individual tree performance from the time of planting until maturation. Four operating strategies were investigated and the profit maximizing and cost minimizing strategies were found to be significant. Evaluation of market selling prices indicated that the profit maximizing strategy was optimal except at very low market prices where the cost minimization strategy was optimal. Price sensitivity for water and fertilizer resources was investigated. Operating strategies were not affected by water price increases over the foreseeable future, however, price changes in nitrogen and phosphorous were found to affect the optimal operating strategy primarily through the substitution of manure in the system. Existing horticultural practices in the Yuma growing area were confirmed by the research. Additional optimal operating strategies were suggested relative to market prices. The long run policy decision making process for orchard managers was enhanced.

Value-at-Risk (VaR) model fails to predict financial risk accurately especially during financial crises. This is mainly due to the model’s inability to calibrate new market information and the fact that the risk measure is characterised by poor tail risk quantification. An alternative approach which comprises of the Expected Shortfall measure and the Lognormal Jump-Diffusion (LJD) model has been developed to address the aforementioned shortcomings of VaR. This model is called the Simulated-Expected-Shortfall (SES) model. The Maximum Likelihood Estimation (MLE) approach is used in determining the parameters of the LJD model since it’s more reliable and authenticable when compared to other nonconventional parameters estimation approaches mentioned in other literature studies. These parameters are then plugged into the LJD model, which is simulated multiple times in generating the new loss dataset used in the developed model. This SES model is statistically conservative when compared to peers which means it’s more reliable in predicting financial risk especially during a financial crisis. / Statistics / M.Sc. (Statistics)

This research has undertaken two key mandates. One was to develop modifications to the African Catchment Game (ACG), a role playing simulation game, in order to simulate rainfall and water management processes representative of the southern African context. The other was to understand what, if any, learning associated with water management issues had taken place as a result of playing the ACG. The modification process took the form of an action research process. The initial modifications were trialed with South African students as part of their undergraduate Geography course offered at Rhodes University, South Africa. Subsequent modifications were implemented over a five month period with three diverse participant groups, namely Finnish, American and South African participants. An interpretive research orientation was employed in order to analyse both the qualitative and quantitative data that was generated. Pre- and Post-Game Questionnaires were used in order to identify the learning and understanding which the participants constructed as a result of playing the ACG. The Chi-Square Test was also applied to each of the pre- and post- questions to establish statistical significance. Subsequent analysis of these questions identified and traced patters and trends associated with learning and understanding across the three game runs. This research study draws on social constructivism and experiential learning as the dominant education theory that underpins it. Results revealed that for all three game runs learning took place. Participants identified dominant themes and environmental dimensions both before and after playing the ACG. The analysis of these responses indicated a deeper awareness of water as a contributing factor for sustainable economic development while the game runs enabled the researcher to adjust the water availability within each game run until rainfall and water management processes representative of a southern African context were successfully simulated in the last game run.