The focus of this chapter on solving unconstrained optimization problems using only function values without utilizing any derivative information. Unconstrained optimization is a class of optimization techniques where the solution of the n-dimensional problem can be any point in the whole parameter space x*∊2 <n.

Chapter Contents:

• 5.1 Why unconstrained optimization?
• 5.2 Classification of unconstrained optimization techniques
• 5.3 The random jump technique
• 5.4 The random walk method
• 5.5 Grid search method
• 5.6 The univariate method
• 5.7 The pattern search method
• 5.8 The Simplex method
• 5.9 Response surface approximation
• A5.1 Electrical application: impedance transformers
• A5.2 Electrical application: the design of photonic devices
• References
• Problems

Inspec keywords: optimisation

Other keywords: derivative-free unconstrained techniques; unconstrained optimization problems; parameter space; n-dimensional problem

Subjects: Optimisation; Optimisation techniques; Optimisation techniques