资 源 简 介
This software package provides a reasonably high performing implementation of estimation-based local search (iterative improvement) algorithm to tackle the Probabilistic Traveling Salesman Problem (PTSP).
The PTSP is a paradigmatic example of a stochastic combinatorial optimization problem. Estimation-based local search (2.5-opt-EEais) is currently the state-of-the-art iterative improvement algorithm for the PTSP that starts from some initial solution and repeatedly tries to move from a current solution to a lower cost neighboring one. The search terminates in a local optimum, that is, a solution that does not have any improving neighbor. A peculiarity of 2.5-opt-EEais is that the cost of the neighboring solutions are estimated using delta evaluation, a technique that considers only the cost contribution of solution components that are not common between two neighbor solutions. The high performance of this algorithm can be attributed to the adoption of the 2.5-exchange neigh
