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A Myopic Capital Budgeting Model**

Published online by Cambridge University Press:  19 October 2009

William T. Ziemba
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Extract

The classic 1955 paper of Lorie and Savage has stimulated the development of mathematical programming approaches to the analysis of capital budgeting problems. A problem that they considered has been succinctly stated as:

given the net present value of a set of independent investment alternatives, and given the required outlays for the projects in each of two time periods, find the subset of projects which maximizes the total net present value of the accepted ones while simultaneously satisfying a constraint on the outlays in each of the two periods.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 4 , Issue 3 , September 1969 , pp. 305 - 327
Copyright
Copyright © School of Business Administration, University of Washington 1969

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References

1.Balas, E., “Extension de l'algorithme additif a la programmation en nombres entiers et a la programmation non lineaire”, Compute Rendus Acadmie Science, CCLVIII, pp. 5136–5139.Google Scholar
2.Balas, E., Duality in Discrete Programming: IV. Applications, Management Sciences Research Report No. 195 (Pittsburgh: Carnegie-Mellon University, October 1968).Google Scholar
3.Balinski, M. L., “Integer Programming: Methods, Uses, Computations”, Management Science XII (1965), pp. 253–313.CrossRefGoogle Scholar
4.Baumol, W. J., and Quandt, R. E., “Investment and Discount Rates Under Capital Rationing — A Programming Approach”, The Economic Journal LXXV (1965), pp. 317–329.CrossRefGoogle Scholar
5.Beale, E. M. L., and Small, R. E., “Mixed Integer Programming by a Branch and Bound Technique,” IFIP Congress, 1965.Google Scholar
6.Bernhard, R. H., “Mathematical Programming Models for Capital Budgeting — A Survey, Generalization, and Critique”, Journal of Financial and Quantitative Analysis, Vol. IV (1969), pp. 111–158.CrossRefGoogle Scholar
7.Byrne, R., Charnes, A., Cooper, W. W., and Kortanek, K., “A Chance-Constrained Approach to Capital Budgeting with Portfolio Type Payback and Liquidity Constraints and Horizon Posture Controls”, Journal of Financial and Quantitative Analysis, Vol. II (1967), pp. 339–364.CrossRefGoogle Scholar
8.Charnes, A., Cooper, W. W., and Miller, M., “Application of Linear Programming to Financial Budgeting and the Costing of Funds”, Journal of Business XXXII (1959), pp. 20–46.CrossRefGoogle Scholar
9.Dakin, R. J., “A Tree Search Algorithm for Mixed Integer Programming Problems”, The Computer Journal, VIII (1965), pp. 250–255.CrossRefGoogle Scholar
10.Driebeck, N. J., “An Algorithm for the Solution of Mixed Integer Programming Problems”, Management Science XII (1966), pp. 576–587.CrossRefGoogle Scholar
11.Eisner, M. J., Kaplan, R. S., and Soden, R. V., Admissable Decision Rules for the E-Model of Chance-Constrained Programming, Technical Report No. 47 (Ithaca, N.Y.: Cornell University, Department of Operations Research, June 1968).Google Scholar
12.Flacco, A. V., and McCormick, G. P., Non-linear Programming: Sequential Unconstrained Minimization Techniques (New York: John Wiley and Sons, Inc., 1968).Google Scholar
13.Geoffrion, A. M., “Integer Programming by Implicit Enumeration and Balas1 Method”, SIAM Review IX (1967), pp. 178–190.CrossRefGoogle Scholar
14.Gordon, M. J., The Investment, Financing and Valuation of the Corporation (Homewood, Ill.: Richard D. Irwin, Inc., 1962).Google Scholar
15.Kaplan, S., “Solution of the Lorie-Savage and Similar Integer Programming Problems by the Generalized Lagrange Multiplier Method”, Operations Research XIV (1966), pp. 1130–1136.CrossRefGoogle Scholar
16.Kolesar, P. J., “A Branch and Bound Algorithm for the Knapsack Problem”, Management Science XIII (1967), pp. 723–735.CrossRefGoogle Scholar
17.Lawler, E. L., and Wood, D. E., “Branch and Bound Methods: A Survey”, Operations Research XIV (1966), pp. 669–719.Google Scholar
18.Lemke, C. E., and Spielberg, K., “Direct Search Algorithms for Zero-One and Mixed Integer Programming”, Operations Research XV (1967), pp. 892–914.CrossRefGoogle Scholar
19.Lorie, J., and Savage, L. J., “Three Problems in Capital Rationing”, Journal of Business XXVIII (1955), pp. 229–239.CrossRefGoogle Scholar
20.Little, J. D. C., et al. , “An Algorithm for the Travelling Salesman Problem”, Operations Research XI (1963), pp. 972–989.CrossRefGoogle Scholar
21.Näslund, B., “A Model of Capital Budgeting Under Risk”, Journal of Business XXXIX (1966), pp. 257–271.CrossRefGoogle Scholar
22.Manne, A., “Optimal Policies for a Self Financing Business Enterprise”, Management Science XV (1968), pp. 119–129.CrossRefGoogle Scholar
23.Mitten, L. G., “Branch and Bound Methods: General Formulation and Properties,” Operations Research. To appear.Google Scholar
24.Weingartner, H. M., Mathematical Programming and the Analysis of Capital Budgeting Problems, Prentice-Hall, Inc., 1963.Google Scholar
25.Weingartner, H. M., “Capital Budgeting of Interrelated Projects: Survey and Synthesis”, Management Science XII (1966), pp. 485–516.CrossRefGoogle Scholar
26.Weingartner, H. M., “Criteria for Programming Investment Project Selection”, The Journal of Industrial Economics XV (1966), pp. 65–76.CrossRefGoogle Scholar
27.Weingartner, H. M., and Ness, D. M., “Methods of Solution of the 0/1 Knapsack Problems”, Operations Research XV (1967), pp. 83–103.CrossRefGoogle Scholar
28.Zangwill, W. I., Nonlinear Programming: A Unified Approach (Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1969).Google Scholar
29.Ziemba, W. T., Solving Random Dynamic Programs by Nonlinear Programming, Faculty of Commerce and Business Administration, Working Paper No. 24 (Vancouver: University of British Columbia, January 1969).Google Scholar