[PDF] Mathematical Programming And The Analysis Of Capital Budgeting Problems eBook

Author : Esra Baş
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Page : pages
File Size : 17,46 MB
Release : 2008
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Capital budgeting problems are linear or non-linear programming models that address the solution of the level of investment in projects by considering basically budget limits. Additional constraints such as borrowing limit constraint or scarce resource constraint are also possible. In this thesis, we study the uncertainty in different capital rationing and capital budgeting problems by considering fuzzy and robust optimization approaches. Fuzzy mathematical programming includes the defuzzification of a fuzzy model by using a fuzzy relation, and analysis and solution of the model by using deterministic mathematical programming techniques. On the other hand, robust optimization approach includes the best solution of the model by considering the worst realization of the uncertain parameters. Although both approaches are devoted to the solution of the models by considering uncertainty , a model solved by fuzzy mathematical programming does not necessarily have to be robust. In this thesis, we. first examine the fuzzy mathematical programming approaches to the Lorie-Savage capital rationing model in the literature, and illustrate the models with the numerical examples. In the other sections devoted to the fuzzy optimization, we propose the defuzzification of Weingartner's pure capital rationing model by triangular norm (t-norm) fuzzy relation and Bernhard's model by t-norm and triangular conorm (t-conorm) fuzzy relations and their detailed analysis. We also propose the decision rules for intemal rate of retum (IRR) in case of cash flow uncertainty .In the chapters devoted to robust optimization, we extend the robust optimization approach to W eingartner' s pure capital rationing and horizon capital budgeting models proposed in the literature by considering additional parameters as uncertain. We also redefine the decision rules of investment appraisal techniques for simple projects analogous to robust optimization. All model propositions are accompanied by computation analysis, which proves the applicability and practicality of the proposed models.

Author : Michael George Headly
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Page : 154 pages
File Size : 40,37 MB
Release : 1980
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A multiple objective fuzzy liner programming approach to the capital budgeting problem is developed. Since much of the available data in any capital budgeting decision situation is either of an imprecise or ill-defined nature, a mathematical optimization technique is required that is capable of incorporating this inherent uncertainty. Fuzzy linear programming provides an effective methodology for this analysis. Specifically, a mathematical model is developed which utilizes fuzzy linear programming as a solution technique for the research and development program or project selection problem. In addition an exchange heuristic, a modified form of C.C. Peterson's exchange algorithm, is presented. A limited bibliography of works in multiple objective optimization is presented. Two computer codes are included. The first utilizes the IBM MPSX/Mixed Integer Programming procedures to solve the (0-1) linear integer programming problem. The second is a FORTRAN program to solve the exchange heuristic algorithm discussed previously. (Author).