Capital Budgeting of Interrelated Projects: Survey and Synthesis

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Abstract
As capital budgeting decision procedures become more complex, they must allow for more aspects of the real world. The present article surveys the techniques available to handle the important and generally neglected problem of project interrelationships such as mutual exclusion and interdependencies. The techniques utilized are linear and integer programming, dynamic programing, and the discrete optimizing procedure of Reiter. Project interrelationships arising from randomness of outcomes and nonlinear utility functions are also subjected to scrutiny by application of these procedures, and additional interrelationships, arising in the context of research and development budgets, are analyzed. A dynamic programming code for the multidimensional 0-1 knapsack problem is also presented.

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