Monthly Archives: November 2012

Particle Swarm Optimization and General Pattern Search

My post-doc supervisor is using a hybridization of particle swarm with a general pattern search for his oil well placement and parameterization optimization problem. PSO and GPS is described below: PSO Particle Swarm Optimization is a gradient free optimization method

Posted in Optimization Algorithms

BFGS – Gradient Approximation Methods

The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is the most commonly used update strategy for implementing a Quasi-Newtown optimization technique. Newton’s method was first derived as a numerical technique for solving for the roots of a nonlinear equation. Newton’s Method solves for the

Posted in Optimization Algorithms

Implicit Filtering – Thank You C.T. Kelley

Implicit Filtering (IF) (designed by C.T. Kelley) is a sophisticated, deterministic pattern search method for bound constrained optimization. Like most pattern search algorithms, the evaluation of the objective function at time step i is used to determine the next cluster

Posted in Optimization Algorithms