Optimal Selection Strategy for the Group Interview Problem
研究了群体面试问题，即每组包含多个候选人的顺序评估场景，推导出最大化选中最佳人选概率的最优策略，并针对组序列优化问题开发了启发式算法，经蒙特卡洛模拟验证其解接近最优（误差在5%以内）。
ABSTRACT We propose a more generalized version of the secretary problem, called the group interview problem, in which each group contains several alternatives and each group of alternatives is presented and evaluated sequentially over time. Using the assumptions corresponding to the classical secretary problem, we derive an optimal selection strategy which maximizes the probability of winning or selecting the single best choice in a given sequence of groups. We further address the problem of choosing at the beginning of the evaluation process a sequence of groups to maximize the winning probability. Because of formidable computational requirements to obtain an optimal solution to this sequencing problem, we then develop a heuristic algorithm based on several properties inherent in an optimal selection strategy. The heuristic procedure is evaluated experimentally using Monte Carlo simulation and is shown to be effective in obtaining near‐optimal (within 5 percent) solutions.