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Using a Genetic Algorithm to Investigate Taxation Induced Interactions in Capital Budgeting

  • R. H. Berry
  • G. D. Smith

Abstract

The capital budgeting problem, as analysed here, involves selecting a combination of projects from the set of all possible combinations of projects to maximise the net present value of cash flows. The traditional investment appraisal approach of carrying out a project by project analysis and selecting accordingly is invalid because of features of the many current taxation system, which introduce non-linear interdependences between the projects.

Using a serial implementation of the genetic algorithm toolkit GAmeter, we investigate this effect using aspects of the UK taxation system on a set of standard capital budgeting problems and compare the results with those obtained using a more traditional approach and a mixed integer programming approach. The capital budgeting model developed includes features such as “carry forward” of capital allowances, multiple rates of corporation tax and capital rationing constraints. The model can be extended to include other tax features found in many economies.

Keywords

Cash Flow Capital Rationing Capital Budget Taxable Profit Mathematical Programming Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag/Wien 1993

Authors and Affiliations

  • R. H. Berry
    • 1
  • G. D. Smith
    • 1
  1. 1.University of East AngliaNorwichUK

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