A procedure for optimizing development decisions

  • Authors:

  • Stephen Kahne

  • Affiliations:

  • Associate Professor, Department of Electrical Engineering, Director, Hybrid Computer Laboratory, University of Minnesota, Minneapolis, Minnesota 55455, U.S.A.

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 1975

Quantified Score

Hi-index 22.15

Visualization

Abstract

This paper addresses the problem of organizing data and formulating questions to be answered for the purpose of making planning and development decisions. The problem is separated into five distinct parts. Each part is discussed in the context of the planning process and each leads logically to the optimization of development decisions. The five parts are goal definition, establishment of criteria, criteria weighting, alternative rating and alternative ranking. The feature of making development decisions which distinguishes them from other optimization problems is what has been called 'fuzziness'. In any realistic problem formulation, the criteria are not precisely defined; they are fuzzy. The relative importance of each criterion is also fuzzy. Indeed, even when one attempts to rate a particular possible solution, he must deal with fuzzy information. The technique proposed in the paper accounts for this uncertainty in all aspects of the problem and yields probabilistic answers. Thus, when various alternative solutions are proposed for a development problem, the technique yields a probabilistic ranking of the alternatives. Sharper results are obtained if less uncertainty is present in certain parts of the data. However, even in the presence of great uncertainty, realistic problem solutions are obtained. Alternative solutions are rated independent of all others and only after the (fuzzy) ratings are complete are comparative rankings accomplished. Throughout the procedure the realistic uncertainties remain a prominent feature of the procedure.