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

Zheyong Bian and Xiang Liu

Transportation Research Part E: Logistics and Transportation Review, 2018, vol. 115, issue C, 246-266

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.

Keywords: Stochastic orienteering problem; Vehicle routing; Routing adjustment; Monte Carlo simulation; Multiple plan approach (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.tre.2018.05.004

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