Abstract

An improvement over an earlier feasible directions minimization algorithm is presented. In a certain sense the new feasible descent cone algorithm is shown to be a generalization of Rosen's gradient projection method. The algorithm is evaluated for linear programming test problems, and promising results are obtained for random problems and problems involving weight minimization of plane trusses.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.