8. Nonlinear Programming

  1. Kenneth R. Baker

Published Online: 7 MAR 2011

DOI: 10.1002/9780470949108.ch8

Optimization Modeling with Spreadsheets, Second Edition

Optimization Modeling with Spreadsheets, Second Edition

How to Cite

Baker, K. R. (2011) Nonlinear Programming, in Optimization Modeling with Spreadsheets, Second Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470949108.ch8

Author Information

  1. Tuck School of Business, Dartmouth College, Hanover, NH, USA

Publication History

  1. Published Online: 7 MAR 2011
  2. Published Print: 4 APR 2011

ISBN Information

Print ISBN: 9780470928639

Online ISBN: 9780470949108

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Keywords:

  • constraint;
  • decision variable;
  • generalized reduced gradient (GRE);
  • nonlinear programming problems;
  • objective function

Summary

This chapter returns to the nonlinear solver and examines the types of optimization problems it can handle. Two features are important in this regard. First, in terms of finding solutions, linear programming models are actually a subset of nonlinear programming models. The second feature to keep in mind is that the generalized reduced gradient (GRG) algorithm has limitations as a nonlinear solver. The nonlinear programming problems contain decision variables, an objective function, and usually some constraints. The chapter looks at problems that have no constraints, so that the author focuses on the nature of a nonlinear objective function and its implications for the use of the nonlinear solver. It also looks at problems with nonlinear objectives and linear constraints. The chapter describes the boundary of linear and nonlinear models. It ends with illustrative examples and followed by a set of practice exercises.

Controlled Vocabulary Terms

Linear programming; Problem solving