Cuckoo search for inverse problems and simulated-driven shape optimization

Issue title: Advances in Simulation-Driven Optimization and Modeling

Guest editors: Slawomir Kozielx, Leifur Leifssonx and Xin-She Yangy

Article type: Research Article

Authors: Yang, Xin-She

Affiliations: Mathematics and Scientific Computing, National Physical Laboratory, UK. Tel./Fax: +44 208 943 6092; E-mail: xin-she.yang@npl.co.uk | [x] Engineering Optimization and Modeling Center, School of Science and Engineering, Reykjavik University, Reykjavik, Iceland | [y] Mathematics and Scientific Computing, National Physical Laboratory, Teddington, UK

Abstract: Most optimization problems rely heavily on simulations to evaluate design solutions according to a set of design criteria under stringent constraints. While an inverse problem may also rely on simulation-driven methods, it can sometimes be viewed more properly as a constrained optimization problem because the main aim of inversion is to find the best parameter estimates so as to minimize the differences between predicted results and observations. In this paper, we will take a unified approach to inversion and optimization. We use the latest cuckoo search to solve inverse problems and shape optimization in heat transfer applications. Simulation results show that cuckoo search is also very efficient for inversion.

Keywords: Cuckoo search, inverse problems, optimization, metaheuristic, shape optimization

DOI: 10.3233/JCM-2012-0408

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 12, no. 1-2, pp. 129-137, 2012