Browsing by Author "Moolman, George Christiaan"

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    An aggregate capital budgeting model using a product portfolio approach
    Moolman, George Christiaan (Virginia Tech, 1994)
    A product portfolio approach is used in this dissertation to develop a model permitting capital budgeting to be modeled interactively with aggregate production planning, in light of market supply and demand functions. Primary emphasis is on the maximization of profit, but other goals are also addressed. These are maximization of the rate of return, maximization of market share, and minimization of the cost of excess capacity. A linear mixed integer programming model is developed for each of these objectives. Then, a single goal programming model that combines all four objectives is formulated. Costs are not allocated to products. Accordingly, the notion of cash flows per product (or per project) is not used. Instead, cost is incurred as a result of the demand that a product portfolio places on resources. All costs are considered to be incurred in the acquisition and utilization (in the form of activities) of resources. Four distinct levels of activities are considered: unit, batch, product sustaining, and facility sustaining. The demand for each resource is aggregated over all levels of variability and over all the products in the product portfolio. The direct cash outflow or inflow as a result of changing resource capacity is continuously traded off against the eventual cost or benefit of changing the capacity (in the form of changed revenues and as a function of both time and market supply and demand). Capital structure and capital investment decisions are considered simultaneously for a given set of assumptions. Different sources of funds are utilized for different costs of capital. Lending and borrowing are simultaneously incorporated without the solutions becoming inconsistent due to incorrect or inappropriate discount factors. This is mainly attributable to the fact that the organization, as a single entity that manufactures a product portfolio, demands capital, and invests excess funds. The net present value of the organization (not of projects or products) is maximized. Also, the output of each project is modeled specifically. This alleviates the practical problem of fractional acceptance of projects. Variable market supply and demand functions are also included and modeled explicitly. Finally, it is shown that the developed model contains several elements of aggregate production planning. The main conclusions from this research are: 1) Better capital budgeting results can be obtained if costs are not allocated to projects (or products) when resources are shared among different projects or products; 2) Financing and investment decisions can be made interactively (with the developed model) without the solutions becoming inconsistent due to unknown discount rates; 3) Resource acquisition and resource consumption should be modeled explicitly in capital budgeting; and 4) The model yields an improvement over existing capital budgeting techniques for a given set of assumptions. Some recommendations are presented for further research to extend these conclusions.
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    A relational database management systems approach to system design
    Moolman, George Christiaan (Virginia Tech, 1992)
    Systems are developed to fulfill certain requirements. Several system design configurations usually can fulfill the technical requirements, but at different equivalent life-cycle costs. The problem is how to manipulate and evaluate different system configurations so that the required system effectiveness can be achieved at a minimum equivalent cost. It is also important to have a good definition of all the major consequences of each design configuration. For each alternative configuration considered, it is useful to know the number of units to deploy, the inventory and other logistic requirements, as well as the sensitivity of the system to changes in input variable values. An intelligent relational database management system is defined to solve the problem described. Table structures are defined to maintain the required data elements and algorithms are constructed to manipulate the data to provide the necessary information. The methodology is as follows: Customer requirements are analyzed in functional terms. Feasible design alternatives are considered and defined as system design configurations. The reliability characteristics of each system configuration are determined, initially from a system-level allocation, and later determined from test and evaluation data. A maintenance analysis is conducted to determine the inventory requirements (using reliability data) and the other logistic requirements for each design configuration. A vector of effectiveness measures can be developed for each customer, depending on objectives, constraints, and risks. These effectiveness measures, consisting of a combination of performance and cost measures, are used to aid in objectively deciding which alternative is preferred. Relationships are defined between the user requirements, the reliability and maintainability of the system, the number of units deployed, the inventory level, and other logistic characteristics of the system. A heuristic procedure is developed to interactively manipulate these parameters to obtain a good solution to the problem with technical performance and cost measures as criteria. Although it is not guaranteed that the optimal solution will be found, a feasible solution close to the optimal will be found. Eventually the user will have, at any time, the ability to change the value of any parameter modeled. The impact on the total system will subsequently be made visible.