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

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  • Bian, Zheyong
  • Liu, Xiang

Abstract

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.

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  • Bian, Zheyong & Liu, Xiang, 2018. "A real-time adjustment strategy for the operational level stochastic orienteering problem: A simulation-aided optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 246-266.
    • Handle: RePEc:eee:transe:v:115:y:2018:i:c:p:246-266
    DOI: 10.1016/j.tre.2018.05.004
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