This paper presents a sequential quadratic programming algorithm for computing a stationary point of a mathematical program with linear complementarity constraints. The algorithm is based on a reformulation of the complementarity condition as a system of semismooth equations by means of Fischer-Burmeister functional, combined with a classical penalty function method for solving constrained optimization problems. Global convergence of the algorithm is established under appropriate assumptions. Some preliminary computational results are reported.
Bibliographical noteFunding Information:
This work was based on research supported partly by a Japan-US collaborative grant awarded to the first and third authors, respectively, by the Japan Society for the Promotion of Science and the U.S. National Science Foundation under grant INT-9417085. The first author’s research was also supported in part by the Scientific Research Grant-in-Aid from the Ministry of Education, Science, Sports, and Culture of Japan. The second author’s research was supported by the Natural Sciences and Engineering Research Council of Canada. The third author’s research was also supported by the U.S. National Science Foundation under grants CCR-9213739 and CCR-9624018.
- Linear complementarity
- Mathematical programs with equilibrium constraints
- Sequential quadratic programming