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

This research looks at designing a product line that maximizes its market s hare for a given set of consumers. Consumer preference data is collected th rough 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 m odels for product line design assumed that purchases are based only on the satisfaction obtained from the product But when products are expensive rela tive to a consumer's budget, the effect of prices and budgets must be consi dered A method for finding solutions to the product line design problem wit h pricing is presented A heuristic based on Genetic Algorithm techniques is developed and tested with simulated data The heuristic results are then an alyzed by comparing them to optimal solutions found through complete enumer ation, and sensitivity analysis of the heuristic parameters is performed Significance: This research presents an efficient method based on Genetic A lgorithm techniques for finding good solutions to difficult problems in pro duct line design using consumer preference data. A model is used that takes into account attribute level prices, consumer budgets constraints, and min imum attribute threshold values for each consumer.