Electronic Proceedings of the Sixteenth Annual International Conference on Technology in Collegiate Mathematics

Chicago, Illinois, October 30-November 2, 2003

Paper S018

This is an electronic reprint, reproduced by permission of Pearson Education Inc. Originally appeared in the Proceedings of the Sixteenth Annual International Conference on Technology in Collegiate Mathematics, Edited by Corinna Mansfield, ISBN 0-321-30456-x, Copyright (C) 2005 by Addison-Wesley Publishing Company, Inc.


Comparison of NLP Search Methods in Nonlinear Optimization Using MAPLE

William P. Fox


Department of Mathematics
Francis Marion University
Florence, SC 29501
USA


list of all papers by this author

William H. Richardson


Department of Mathematics
Francis Marion University
Florence, SC 29501
USA


list of all papers by this author

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ABSTRACT

Need an optimization process for a nonlinear multivariable function? Implementing classic optimization algorithms like steepest ascent, Newton's Method, and the conjugate method in Maple can strike a valuable compromise between tediously grinding out step-by-step approximations with a calculator and using a 'canned' optimization package.

Keyword(s): optimization, Maple