<div>This paper reviews some real-world problems modeling</div>


<div>as Probabilistic Traveling Salesman Problem (PTSP), by</div>


<div>presenting the important results found in the literature. It</div>


<div>illustrates the usefulness of the inclusion of probabilistic elements in
deterministic models. We propose a new modeling of the PTSP by the
deviations of the routing of a robot in order to avoid obstacles which
are not foreseen in its path. The Probabilistic Traveling Salesman
Problem(PTSP) is a variation of the classic Traveling Salesman Problem
(TSP) where each node i is present</div>


<div>with probability pi. The solution for the PTSP consists in finding an a
priori tour that visits all the cities that minimizes the expected
length of the tour. From the litterateur the PTSP is NP-Complete,
therefore the execution time is a prime factor in its resolution. In the
last of his paper we present a new parallel Tabu search heuristic for
solving PTSP by using the Open MPI environment.</div>