<p> Three chapters comprise this project. The first chapter deals with the global picture of energy supply and demand, and concludes that other sources of energy must be developed in the next fifty years.</p> <p> Chapter Two considers a number of alternate sources of energy and examines two sources in particular: (i) Hydrogen and its dependence on electricity, and (ii) Nuclear energy used to produce electricity. Certainly, Ontario has a very viable option to produce electricity by means of nuclear energy.</p> <p> Home heating can, to some extent, be controlled by the individual, and Chapter Three discusses the operation of a heat pump and its feasibility as a heating device for homes in the Southern Ontario climate.</p> / Thesis / Master of Science (Teaching)

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No / In this paper a simple model is presented that considers the factors influencing male decisions concerning whether or not to consume, at the margin, female prostitution services. Data from an extensively piloted and sophisticated national survey of sexual attitudes and lifestyles were used to test the predictions. Health risks of consumption, religious denomination and factors signalling variations in inherent risk disposition are shown to explain consumption of such services.

Prior to 1996, roughly 70% of electricity service in California was provided by investor owned utilities (IOUs). The IOUs operated as monopolies in their respective service territories, performing all of the functions necessary to generate and deliver electricity to the consumer. In exchange for service, the IOUs were paid a regulated rate which was designed to recover their cost of providing the service plus a reasonable return on their investment. In 1996, California changed the way electric service was provided in order to make it more competitive. Among the changes, utilities would procure their supplies at market prices in an auction or spot market; residential customers could choose their electric supplier; and residential rates were frozen at 10% below their June 1996 levels. The rate freeze was to remain in effect until the later of March 31, 2002, or the date the IOUs fully recovered certain expenses that were still on their books (i.e., stranded costs). The restructured market commenced operations on March 31, 1998. During the summer of 2000, California experienced record increases in wholesale prices and supply shortages that ultimately resulted in a number of rolling blackouts. Most of California?s residential customers were unaffected by the increased wholesale prices because their rates remained frozen. Regulators and others who have studied what went wrong during the summer of 2000 in California agree that the increase in wholesale prices was due to a combination of factors, one of which was the residential rate freeze. This thesis proposes to show how fixing the price of electricity resulted in excess demand and to quantify the size of the excess. This thesis also shows how much of a price increase would have been needed to prevent the shortages. / Master of Arts

The purpose of this research project was to evaluate the techniques outlined in the National Cooperative Highway Research Program Technical Report 255 Highway Traffic Data for Urbanized Area Project Planning and Design (NCHRP-255), published in 1982 by the Transportation Research Board. This evaluation was accomplished by using a regional travel demand forecast model calibrated and validated for the year 1990 and developing a highway forecast for the year 2000. The forecasted volumes along the Capital Beltway (I-495/I-95) portion located in the State of Maryland were compared to observed count data for that same year. A series of statistical measures were used to quantitatively evaluate the benefits of the techniques documented in NCHRP-255. The primary research objectives were: • To critically evaluate the ability of a regional travel demand forecast model to accurately forecast freeway corridor volumes by comparing link forecast volumes to the actual count data. • To evaluate and determine the significance of post-processing techniques as outlined in NCHRP-255. The most important lesson learned from this research is that although it was originally written in 1982, NCHRP-255 is still a very valuable resources for supplementing travel demand forecast model output. The "raw" model output is not reliable enough to be used directly for highway design, operational analysis, nor alternative or economic evaluations. The travel demand forecast model is a tool that is just part of the forecasting process. It is not a turn-key operation, and travel demand forecasts cannot be done without the application of engineering judgment. / Master of Science

Typescript (photocopy). / Digitized by Kansas Correctional Industries

This thesis explores forecasting for intermittent demand requirements. Intermittent demand occurs at random, with some time periods showing no demand. In addition, demand, when it occurs, may not be for a single unit or a constant size. Consequently, intermittent demand creates significant problems in the supply and manufacturing environment as far as forecasting and inventory control are concerned. A certain confusion is shared amongst academics and practitioners about how intermittent demand (or indeed any other demand pattern that cannot be reasonably represented by the normal distribution) is defined. As such, we first construct a framework that aims at facilitating the conceptual categorisation of what is termed, for the purposes of this research, “non-normal” demand patterns. Croston (1972) proposed a method according to which intermittent demand estimates can be built from constituent elements, namely the demand size and inter-demand interval. The method has been claimed to provide unbiased estimates and it is regarded as the “standard” approach to dealing with intermittence. In this thesis we show that Croston’s method is biased. The bias is quantified and two new estimation procedures are developed based on Croston’s concept of considering both demand sizes and inter-demand intervals. Consequently the issue of variability of the intermittent demand estimates is explored and finally Mean Square Error (MSE) expressions are derived for all the methods discussed in the thesis. The issue of categorisation of the demand patterns has not received sufficient academic attention thus far, even though, from the practitioner’s standpoint it is appealing to switch from one estimator to the other according to the characteristics of the demand series under concern. Algebraic comparisons of MSE expressions result in universally applicable (and theoretically coherent) categorisation rules, based on which, “non-normal” demand patterns can be defined and estimators be selected. All theoretical findings are checked via simulation on theoretically generated demand data. The data is generated upon the same assumptions considered in the theoretical part of the thesis. Finally, results are generated using a large sample of empirical data. Appropriate accuracy measures are selected to assess the forecasting accuracy performance of the estimation procedures discussed in the thesis. Moreover, it is recognised that improvements in forecasting accuracy are of little practical value unless they are translated to an increased customer service level and/or reduced inventory cost. In consequence, an inventory control system is specified and the inventory control performance of the estimators is also assessed on the real data. The system is of the periodic order-up-to-level nature. The empirical results confirm the practical validity and utility of all our theoretical claims and demonstrate the benefits gained when Croston’s method is replaced by an estimator developed during this research, the Approximation method.

The airline industry is a highly competitive market. Particularly after the major liberalization in the industry, the competition carried a step forward for all the concerned companies. Airline industry is a very dynamic market also; the expenses of a single operation may change substantially in a very short time period, which could be due to the fickle regulations or the fluctuation of oil prices. At any time, for a certain destination, a new airline company can start its operations and become a competitor, which can result in a market share loss for current operators. In such an environment, airline companies strive to maximize their revenues in every single flight. Load factors of a flight, classification, and pricing of airline tickets in a flight are determinative on the revenue of a single operation. In order to maximize revenue for its operations, companies should have a broad range of information about airline market conditions and passenger profile and preferences for every destination that they operate. Turkish Airlines, which is the largest airline company of Republic of Turkey and increasing its global awareness day by day, also strives to maximize its revenues per flight. In order to do so, Turkish Airlines needs to have suitable decisions regarding the capacity issues (determination of type and number of aircrafts, and flight frequencies) which will be then used worldwide in the different branches of company. These reasons lead to the increased need for the company to adopt practical total demand analysis in its operating destinations. The company aims to specify the factors, which are effective on the change of total demand for every destination. Turkish Airlines also strives to make most accurate demand forecasting in order to manage the peaks and troughs of the company’s flights. This project was brought to agenda in order to help this company to address this issue and was initiated with the purpose of making a total demand analysis for specified destinations. Destinations are from Stockholm to Athens, Thessalonica, New Delhi, Mumbai, Istanbul, Bangkok, and Dubai. This study is a quantitative study. Chosen demand factors, which constitute the total airline traffic between destination cities, are analyzed with respect to change in total demand. Various demand-forecasting methods are also applied in order to determine the best forecasting method for each destination, which is compatible with the quantitative approach. Results of the study are directly related to the airline market conditions of aforementioned destinations. Results are presented in four subheadings for every destination; overview of airline market, competition level of airline market, factors regarding the destination and demand forecasting for the destination. This study provides important information to Turkish Airlines regarding total demand analysis of specified destinations. Company learns the common factors (price, total amount of luggage, etc.) and the destination specific factors (language of crew, Frequent Flyer Programs, etc.) that are effective on the change of demand. Company may use this information in order to increase its market share (amount of passengers carried in a certain destination by Turkish Airlines from total demand) for specified destinations. With the help of this study, the company can make an accurate demand forecasting for Turkish Airlines’ future flights, which can be used in planning activities like determining the type of aircraft and flight frequency for a destination, and pricing of flight tickets through different passenger segments.