RESEARCH PAPERS: Design Automation Papers

Optimization With Discrete Variables Via Recursive Quadratic Programming: Part 2—Algorithm and Results

[+] Author and Article Information
J. Z. Cha, R. W. Mayne

Mechanical and Aerospace Engineering, SUNY, Buffalo, N.Y.

J. Mech., Trans., and Automation 111(1), 130-136 (Mar 01, 1989) (7 pages) doi:10.1115/1.3258956 History: Received September 01, 1988; Online November 19, 2009


A discrete recursive quadratic programming algorithm is developed for a class of mixed discrete constrained nonlinear programming (MDCNP) problems. The symmetric rank one (SR1) Hessian update formula is used to generate second order information. Also, strategies, such as the watchdog technique (WT), the monotonicity analysis technique (MA), the contour analysis technique (CA), and the restoration of feasibility have been considered. Heuristic aspects of handling discrete variables are treated via the concepts and convergence discussions of Part I. This paper summarizes the details of the algorithm and its implementation. Test results for 25 different problems are presented to allow evaluation of the approach and provide a basis for performance comparison. The results show that the suggested method is a promising one, efficient and robust for the MDCNP problem.

Copyright © 1989 by ASME
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