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|Title: ||Project selection under multi-period capital rationing|
|Authors: ||Peprah, Alex Kwaku|
|Issue Date: ||11-Aug-2008|
|Series/Report no.: ||4969;|
|Abstract: ||Due to insufficient funds available for investment, Municipal Assemblies are unable to initiate or implement all their viable projects. The dilemma facing the Municipal Assemblies is that, which of the numerous projects the management should invest under the limited investment capital in order to maximize profit.
To solve this project selection problem, data were drawn from sources such as financial statements, monthly and annual reports, daily newspapers and other relevant documents of the Sunyani Municipal Assembly over the period 2001-2006. Financial Ratios, Continuous Probability Analysis, Linear and Integer Programming Models were used to analyze the data. Sensitivity analyses were performed on the project parameters.
The Linear Programming Model designed was suitable for solving large scale project selection under multi-period capital rationing problems, and this produces tlje optimal solution quantities (i.e., the project to be initiated), the value of the objective function (i.e., the Net Present Value) and the opportunity cost of the binding constraints. On the other hand, the selection of small scale project problems was found to be solved easily by Integer Programming Models.
The Mathematical models such as linear programming and Integer programming were found to be:
• Suitable for selecting potential projects and maximizing the returns from the batch of projects selected by the Sunyani Municipal Assembly,
• Suitable for carrying out sensitivity analysis on the optimal solution to Linear programming problems to see how sensitive the project selection is to the changes in the parameters of the model.
|Description: ||A thesis submitted to the School of Graduate Studies, Kwame Nkrumah of Science and Technology in partial fulfilment of the requirements for the degree of Master of Science in Industrial Mathematics, 2008|
|Appears in Collections:||Distance Learning|
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