Variations in the efficiency of a mathematical programming solver according to the order of the constraints in the model

It is well-known that the efficiency of mixed integer linear mathematical programming depends on the model (formulation) used. With the same mathematical programming solver, a given problem can be solved in a brief calculation time using one model but requires a long calculation time using another. In this paper a new, unexpected feature to be taken into account is presented: the order of the constraints in the model can change the calculation time of the solver considerably. For a test problem, the Response Time Variability Problem (RTVP), it is shown that the ILOG CPLEX 9.0 optimizer returns a ratio of 17.47 between the maximum and the minimum calculations time necessary to solve optimally 20 instances of the RTVP, according to the order of the constraints in the model. It is shown that the efficiency of the mixed integer linear mathematical programming depends not only on the model (formulation) used, but also on how the information is introduced into the solver.