Markov Chain Anticipation for the Online Traveling Salesman Problem by Simulated Annealing Algorithm

The arc costs are assumed to be online parameters of the network and decisions should be made while the costs of arcs are not known. The policies determine the permitted nodes and arcs to traverse and they are generally defined according to the departure nodes of the current policy nodes. In on-line created tours arc costs are not available for decision makers. The on-line traversed nodes are fixed and unchangeable for the next times. A discrete time Markov chain is established in on-line policy times. Then, the best state is selected to traverse the next node by a simulated annealing heuristic.