Conjoint Optimization: An Exact Branch-and-Bound Algorithm for the Share-of-Choice Problem
提出一种精确的分支定界算法，用于解决联合分析中的选择份额问题，即找到使最多消费者偏好超过保留效用的新产品设计。基于大型商业数据和模拟实验，该算法能有效找到现实规模问题的最优解。
Conjoint analysis is a statistical technique used to elicit partworth utilities for product attributes from consumers to aid in the evaluation of market potential for new products. The objective of the share-of-choice problem (a common approach to new product design) is to find the design that maximizes the number of respondents for whom the new product’s utility exceeds a specific hurdle (reservation utility). We present an exact branch-and-bound algorithm to solve the share-of-choice problem. Our empirical results, based on several large commercial data sets and simulated data from a controlled experiment, suggest that the approach is useful for finding provably optimal solutions to realistically sized problems, including cases where partworths contain estimation error.