Eight. Hybrid Approaches

  1. Matteo Pastorino

Published Online: 26 APR 2010

DOI: 10.1002/9780470602492.ch8

Microwave Imaging

Microwave Imaging

How to Cite

Pastorino, M. (2010) Hybrid Approaches, in Microwave Imaging, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470602492.ch8

Publication History

  1. Published Online: 26 APR 2010
  2. Published Print: 24 MAR 2010

Book Series:

  1. Wiley Series in Microwave and Optical Engineering

Book Series Editors:

  1. Kai Chang

Series Editor Information

  1. Texas A&M University, USA

ISBN Information

Print ISBN: 9780470278000

Online ISBN: 9780470602492

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Keywords:

  • ant colony optimization;
  • hybrid approaches;
  • linear sampling method;
  • memetic algorithm

Summary

This chapter discusses some examples of possible hybrid approaches. Although the definition of a hybrid method is again quite an arbitrary task, some examples are reported in the chapter, with reference to proposals appearing in the scientific literature. The memetic algorithm is an iterative population-based method. During the iterative evolution, only local minima of the cost function are considered. They are obtained by applying a local minimization method to any element of the population. The chapter also discusses the combination of a qualitative method, namely, the linear sampling method, and a quantitative stochastic method, ant colony optimization. The hybrid approach combines the robustness and generality of the linear sampling method, which is able to retrieve the contours of a wide class of scatterers with the capability of escaping from local minima of the ant colony optimization algorithm, which has been found to converge within a reasonably small number of iterations.

Controlled Vocabulary Terms

ant colony optimisation; sampling methods; stochastic processes