A new model and solution method for product line design with pricing

Existing customer preference based product design models do not consider pr oduct prices and consumer budgets. These models assume that a purchase is b ased only on the satisfaction obtained from the product, irrespective of th e product price and customer budget. However, when products are expensive r elative to buyers' budgets, the effect of prices and budgets must be consid ered in addition to customer satisfaction. Most current models, moreover, a ssume that a low preference for one product characteristic is compensated b y high preference for another, which may not hold for unacceptable levels o f characteristics. For such products, we incorporate prices, budget constra ints, and minimum acceptable thresholds in our model. To solve the model we develop a highly accurate, robust and efficient Beam Search (BS) based heu ristic that identifies optimal or near optimal product lines. The heuristic is rested on 300 simulated problems and an application. It is also compare d to a Genetic Algorithms (GA) based heuristic. We found that our heuristic worked better than the GA heuristic in identifying optimal and near optima l solutions quickly. We also give detailed examples that illustrate the heu ristic and demonstrate a pricing analysis application of the model.