A real-time adjustment strategy for the operational level stochastic orienteering problem: A simulation-aided optimization approach

摘要

This paper focuses on operational level stochastic orienteering problem, in which travel time and service time are stochastic and the vehicle can adjust its routing plan. A real-time adjustment strategy, called Simulation-Aided Multiple Plan Approach (SMPA), is proposed to optimize the real-time vehicle routing plan. We embed a "myopia prevention" strategy into SMPA to improve solution quality. The numerical experiment compares the performance of our proposed algorithm with a strategic level algorithm and another commonly used operational level algorithm called re-optimization algorithm. The results show that our algorithm outperforms previous methods in both solution quality and computing time.