Computer experiments on quadratic programming algorithms

This paper compares the computational performance of five quadratic programming algorithms. These include Wolfe's simplex method, Lemke's complementary pivot method, convex simplex method and quadratic differential algorithm. Execution time and iteration count are used as the major criteria for comparison. Since Lemke's algorithm out-performed all other methods in the study, a detailed statistical analysis was performed to determine the relative importance of problem parameters on the efficiency of Lemke's algorithm. An analysis of variance showed that the number of variables, the percent of positive linear terms in the objective, the number of constraints, and their interactions were the significant factors for both iteration count and execution time. Finally, regression equations for iteration count and execution time are derived as a function of fifteen problem parameters.