Finding the k reliable shortest paths under travel time uncertainty

• The K reliable shortest paths problem is formulated for finding K α-reliable paths in stochastic networks.• Deviation path concept is established for solving the K α-reliable paths problem.• A deviation path algorithm is proposed to exactly solve the K reliable shortest paths problem.• The A* technique is introduced to improve the computational performance of the proposed algorithm.• Comprehensive case study is performed to validate the proposed algorithms.

This paper investigates the problem of finding the K reliable shortest paths (KRSP) in stochastic networks under travel time uncertainty. The KRSP problem extends the classical K loopless shortest paths problem to the stochastic networks by explicitly considering travel time reliability. In this study, a deviation path approach is established for finding K α-reliable paths in stochastic networks. A deviation path algorithm is proposed to exactly solve the KRSP problem in large-scale networks. The A* technique is introduced to further improve the KRSP finding performance. A case study using real traffic information is performed to validate the proposed algorithm. The results indicate that the proposed algorithm can determine KRSP under various travel time reliability values within reasonable computational times. The introduced A* technique can significantly improve KRSP finding performance.