Solving the product line design with pricing problem using genetic algorithm techniques

This research looks at designing a product line that maximizes its market share for a given set of consumers. Consumer preference data are collected through conjoint analysis. A product line design model is used that includes attribute level prices, consumer budget constraints and minimum attribute threshold values for each consumer. This model is unique in that previous models for product line design assumed that purchases are based only on the satisfaction obtained from the product. But when products are expensive relative to a consumer's budget, the effect of prices and budgets must be considered. A method for finding solutions to the product line design problem with pricing is presented. A heuristic based on Genetic Algorithm techniques is developed and tested with simulated data. The heuristic results are then analyzed by comparing them to optimal solutions found through complete enumeration, and sensitivity analysis of the heuristic parameters is performed.