A Branch-and-Price Approach to the Share-of-Choice Product Line Design Problem
开发了一种分支定价算法，利用选择型联合分析的部分效用估计来构建最优产品线，以最大化选择份额，并通过大规模数据验证了算法在现实问题中的最优性和鲁棒性。
We develop a branch-and-price algorithm for constructing an optimal product line using partworth estimates from choice-based conjoint analysis. The algorithm determines the specific attribute levels for each multiattribute product in a set of products to maximize the resulting product line's share of choice, i.e., the number of respondents for whom at least one new product's utility exceeds the respondent's reservation utility. Computational results using large commercial and simulated data sets demonstrate that the algorithm can identify provably optimal, robust solutions to realistically sized problems.