The strong network orientation problem

This study presents models and heuristics for solving the strong network orientation problem (SNOP), which can model several tactical optimization problems of setting directions in urban networks. The objective is to set an each edge undirected graph such that resulting digraph strongly connected total travel distance between any pair nodes minimized (or maximized). Investigating as SNOP motivated by challenges networks due growth population areas, large number daily trips, increasing price maintaining networks, need reduce air pollution passive noise. Thus, a new trend utilize better. In this context, we first use multicommodity flow formulation minimization problem. maximization version modeled using dual shortest path Then, scalable heuristic strategies are investigated. For purpose, propose basic components constructive heuristics, perturbations local searches. They combined into metaheuristics based on searches, multi-start evolutionary schemes, i.e. Multistart Local Search, Iterated Search (ILS), Relaxed ILS, Evolutionary (ELS), ELS, Variable Neighborhood Search. Computational experiments have been performed analyze proposed methods terms efficiency quality solutions, grid instances from downtown Clermont-Ferrand France.