TRIANGULATION IN DECISION-SUPPORT SYSTEMS - ALGORITHMS FOR PRODUCT DESIGN

Often complex decision problems requiring decision aids, such as a Dec ision Support System (DSS), do not have solution procedures that can g enerate an optimal solution in a realistic time period. This has led t o the specification of heuristic solution procedures. However, the qua lity of the solution obtained using a heuristic in specific instances can be uncertain and may be open to debate. One approach to increase t he confidence in the quality of the obtained solution is to use the tr iangulation approach recommended and often used in the social sciences . Thus, the result obtained with a specific heuristic can be considere d 'good' (i.e., close to optimal) if that result is in the ball park o f the result obtained through a maximally different method. In other w ords, using very different solution techniques helps provide benchmark s and thus enables the decision maker to avoid those solutions which a re caught in local maxima. Based on this notion we have designed a pro totype GENEtic algorithms based decision support SYStem (GENESYS) for the product design problem. The DSS provides three different solution techniques, specifically, complete enumeration (optimal solution) for small problems, heuristic dynamic programming and genetic algorithms, to address the product design problems.