An Efficient Label-setting Algorithm for the Bi-objective Shortest Path Problem

In this paper, we consider a classical Bi-objective Shortest Path problem (BSP) that takes into account both distance and insecurity criteria. This work is in collaboration with an enterprise who provide a web platform called Géovélo that aims to propose routes for cycling. We propose a new exact method to solve a BSP, called Label Setting algorithm with Dynamic update of Pareto Front (LSDPF), which aims to find all nondominated solutions of the problem. Different exploration strategies have been proposed and tested. Numerical experiments on real data sets and on instances of the literature were conducted. Comparison with recent benchmarks algorithms solving BSP the bounded Label Setting algorithm by (Raith, 2010) and the pulse algorithm by (Duque et al., 2015) shows that our method outperform these benchmarks algorithms.

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