Technician routing and scheduling for the sharing economy
针对共享经济中技能各异的技术人员，提出最小化路径与调度成本的模型，用启发式算法高效求解，发现交叉培训收益有限，专精领域更高效。
Efficient routing and scheduling plans for a modern workforce are challenging to develop for many firms offering services to customers at their home. In this paper, we focus on those firms that provide technical or maintenance related assistance using heterogeneously skilled technicians working in the sharing economy. We present a model that minimizes the costs of routing and scheduling these technicians, operating out of their own homes, serving a set of customers with demand for a variety of tasks revealed on a daily basis over a multi-period planning horizon. We construct this dynamic, stochastic problem as a Markov decision process and introduce a heuristic that takes advantage of problem characteristics to provide solutions efficiently. This heuristic simplifies the model by reducing the goal function and incorporating an approximation for routing cost, effectively and efficiently solving real world sized problems. We use the heuristic to provide insight into managerial decisions associated with managing a team of technicians, showing that the benefit of cross-training technicians has limitations and that in most circumstances it is more efficient to use technicians with focused areas of expertise.