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The most common way in which probabilities are associated with combinatorial optimization problems is to consider that the data of the problem are deterministic (always present) and randomness carries over the relation between these data (for example, randomness on the existence of an edge linking two vertices in the framework of a random graph theory problem ([BOL 85]) or randomness on the fact that an element is included to a set or not, when dealing with optimization problems on set-systems or, even, randomness on the execution time of a task in scheduling problems). Then, in order to solve an optimization problem, algorithms (probabilistic or, more frequently, deterministic) are. | Probabilistic Combinatorial Optimization on Graphs Cécile Murat and Vangelis Th. Paschos Probabilistic Combinatorial Optimization on Graphs This page intentionally left .
