Decision Support Systems

Decision making involves the selection or choice of alternatives, and is generally based on a combination of empirical information and human judgment. As decision makers, we tend to view problems semantically, and in attempting to automate the process, it is often difficult to translate our semantic understanding of the problem into quantifiable algorithms. The use of fuzzy logic allows decision-making rules to be represented semantically, making the development and review of Decision Support Systems more widely available and understandable to end users.

Some examples of Decision Support Systems or tools include:

Pricing Model Application

One application of fuzzy decision support systems is in determining the unit price for a new product.  This process involves considering a number of imprecise and uncertain factors, many of them unrelated to one another, and others that appear to be entirely contradictory. An example of such a model, developed by Mr. Earl Cox of Metus Systems, can be found in the reference cited below. Sonalysts is available to implement custom decision support systems addressing a wide range of problems found in the fields of micro-economics and finance. 

Reference: Cox, Earl D. (1995) Fuzzy Logic for Business and Industry, Charles River Media, Rockland, MA

Force Realignment Decision Support System

FREDS is an expert system built for the Army National Guard (ARNG) to support determination of which units, in which states, will be inactivated, activated, or reallocated based on changing national requirements. For more information on FREDS, please contact Nadja O'Hagan of Fuzzy Logic, Inc. Sonalysts is available to implement custom decision support systems addressing unique customer requirements. 

Reference: O'Hagan, Nadja K., and O'Hagan, Michael, "Decision-Making with a Fuzzy Logic Inference Engine" (Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE), Volume 2061, 8-10 September 1993).

The Special Operations Forces Mission Effectiveness Model

A mission effectiveness model for determining the mission effectiveness of Navy commandos (SEALs) operating under a range of tactical and environmental conditions. This model uses an expert knowledge-based approach to combining the effect of 18 environmental and tactical factors on different phases of an amphibious tactical mission. Fuzzy logic was used to combine the weighted individual effect of each environmental and tactical factor into a single relative value for mission effectiveness.  

Reference: Cowden, Anthony T.C., "The Special Operations Forces (SOF) Mission Effectiveness Model (MEM): A Fuzzy Logic Decision Support System" (US Army Test and Evaluation Command (TECOM) Artificial Intelligence Technology Symposium (TAITS-96), 12 September 1996).

The Fuzzy Decision Maker

The Fuzzy Decision Maker allows the user to define goals and constraints, and provide them with relative importance weights on a scale of 1 (least) to 9 (most). The user then defines various alternatives, and ranks them independently against the goals and constraints. Again, ranking of the alternative against the goal or constraint is done on a scale of 1 to 9. Finally, the user defines their own optimism-pessimism level, and the software conducts a ranking of the alternatives. The Fuzzy Decision Maker was developed by Fuzzy Logic, Inc., and can be purchased through Fuzzy Systems Engineering. Sonalysts is available to implement custom decision support systems addressing unique customer requirements. 

Reference: McNeill, F. Martin, and Thro, Ellen (1994) Fuzzy Logic: A Practical Approach, AP Professional, Cambridge, MA

For more information E-Mail: FuzzyQuery@Sonalysts.com

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