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Iterative Solution Algorithms for Nonlinear Optimization

In: Optimization in Engineering

Author

Listed:
  • Ramteen Sioshansi

    (The Ohio State University)

  • Antonio J. Conejo

    (The Ohio State University)

Abstract

Chapter 4 introduces optimality conditions to solve nonlinear programming problems (NLPPs). Optimality conditions have the benefit that they allow us to find all points that are candidate local minima, but can be quite cumbersome. For these reasons, in many practical cases NLPPs are solved using iterative algorithms that are implemented on a computer. In this chapter we begin by first introducing a generic iterative algorithm for solving an unconstrained NLPP. We also introduce two broad approaches to solving constrained NLPPs.

Suggested Citation

  • Ramteen Sioshansi & Antonio J. Conejo, 2017. "Iterative Solution Algorithms for Nonlinear Optimization," Springer Optimization and Its Applications, in: Optimization in Engineering, chapter 0, pages 287-336, Springer.
    • Handle: RePEc:spr:spochp:978-3-319-56769-3_5
    DOI: 10.1007/978-3-319-56769-3_5
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