The maximum probability shortest path problem involves the constrained shortest path problem in a given graph where the arcs resources are independent normally distributed random variables. We maximize the probability that all resource constraints are jointly satisfied while the path cost does not exceed a given threshold. We use a second-order cone programming approximation for solving the continuous relaxation problem. In order to solve this stochastic combinatorial problem, a branch-and-bound algorithm is proposed, and numerical examples on randomly generated instances are given.
- Resource constrained shortest path
- Second-order cone programming
- Stochastic programming
ASJC Scopus subject areas
- Discrete Mathematics and Combinatorics
- Applied Mathematics