Abstract

AbstractProduct line design is one of the most important decisions for an organization in today’s hypercompetitive world. Product line designs are NP-hard, which implies that it requires an unacceptable amount of time to obtain the guaranteed optimal solution to a problem of reasonable scale. Machine learning techniques such as genetic algorithms can provide very “good” solutions to these problems. In this chapter, we describe the architecture and user interface of a multi-feature decision support system, PRODLINE, which allows the decision maker to address the decision problem of product line designs. A key feature of the system is its ability to provide users with solutions using different solution techniques as well as the ability to change easily the algorithm parameters to assess if improvements in the solution are possible. A final novel and major advantage of the PRODLINE system is that it permits the user to consider strategic competitive responses to the optimal product line design problem.KeywordsProduct LineDynamic ProgrammingDecision Support SystemAttribute LevelConjoint AnalysisThese 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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