A robust optimization approach for the road network daily maintenance routing problem with uncertain service time

Lu Chen, Michel Gendreau, Minh Hoàng Hà and André Langevin

Transportation Research Part E: Logistics and Transportation Review, 2016, vol. 85, issue C, 40-51

Abstract: This paper studies the robust optimization approach for the routing problem encountered in daily maintenance operations of a road network. The uncertainty of service time is considered. The robust optimization approach yields routes that minimize total cost while being less sensitive to substantial deviations of service times. A robust optimization model is developed and solved by the branch-and-cut method. In computational experiments, the behavior of the robust solutions and their performance are analyzed using Monte Carlo simulation. The robust optimization model is also compared with a classic chance-constrained programming model. The experimental analysis provides managerial insights for decision makers to determine an appropriate routing strategy.

Keywords: Arc routing problem; Robust optimization; Uncertainty; Chance-constrained programming; Branch-and-cut; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.tre.2015.11.006

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