Scheduling with Testing
研究服务环境中在测试（诊断）与处理任务之间动态分配资源的调度问题，通过分析得到最优策略的结构性结果和高效算法，量化了测试的价值。
We study a new class of scheduling problems that capture common settings in service environments, in which one has to serve a collection of jobs that have a priori uncertain attributes (e.g., processing times and priorities) and the service provider has to decide how to dynamically allocate resources (e.g., people, equipment, and time) between testing (diagnosing) jobs to learn more about their respective uncertain attributes and processing jobs. The former could inform future decisions, but could delay the service time for other jobs, while the latter directly advances the processing of the jobs but requires making decisions under uncertainty. Through novel analysis we obtain surprising structural results of optimal policies that provide operational managerial insights, efficient optimal and near-optimal algorithms, and quantification of the value of testing. We believe that our approach will lead to further research to explore this important practical trade-off. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2973 . This paper was accepted by Yinyu Ye, optimization.