Performance of several nonlinear programming software packages on microcomputers

Nonlinear programming (NLP) problems arise often in science, engineering, and business applications. Due to the inherent mathematical limitations of the solution techniques, the existing solution methods are not guaranteed to solve all problems optimally. In the past years, a number of new commercial packages that solve NLP problems on microcomputers have been developed. To grasp some idea of the performance of the NLP packages on microcomputers from the viewpoints of effectiveness, efficiency, accuracy, and ease of use, six popular NLP packages are selected for comparison. The results provide some information regarding the suitable package to use under different considerations. This paper investigates the performance of six NLP packages, including MATLAB, IMSL, AMPL, GAMS, GINO, and SQP, by solving seventy test problems on a PC 486 machine. These packages are categorized as library subroutines, modeling languages, and the conventional NLP codes. The results show that AMPL and GINO have the best ability in solving NLP problems optimally, GAMS is the most efficient package in terms of the execution time, GINO has the most accurate solution, and MATLAB needs the least effort in modeling problems. In sum, GAMS and GINO have the best overall performance, followed by AMPL. All these three packages are of modeling language type.