A pruning heuristic for use with multisource product design
Products can be improved by integrating multiple viewpoints during the design process. A model has been developed that uses conjoint data from consumers and designers and optimizes a product design based on the total share-of-choices. Because the problem becomes very difficult to solve as size increases, a heuristic is developed, based on pruning techniques, to solve the problem to near-optimality in a shorter period of time as compared to complete enumeration. The performance of the heuristic is demonstrated through the use of test data and by comparison to a Genetic Algorithm (GA) based heuristic and Tabu search. Structural results for the heuristic are also provided.
heuristics product design genetic algorithms tabu search conjoint analysis