An Iterated Local Search Algorithm for The Uncertain Orienteering Problem

Orienteering problem is gradually prevalent in the recent decade, but studies considering uncertainties are still at a low pace. First, this paper considers time and benefit as uncertain variables and establishes an uncertain orientation model. Then, based on the uncertainty theory, the model can be transformed into an equivalent form. Then, an iterative local search algorithm is developed for the OP problem. Finally, the effectiveness of the algorithm is verified on the standard datasets, and the influence of the uncertain time on the optimal route of the model is analyzed.