A Hybrid Firefly Algorithm for Constrained optimization and Engineering Application

DOI

10.2991/esac-15.2015.40How to use a DOI?

Keywords

Firefly algorithm, Rosenbrock's local search, Constrained optimization, Engineering application

Abstract

Firefly algorithm (FA) has been recently proposed as a stochastic optimization method and it is has so far been successfully applied in a variety of fields, especially for unconstrained optimization problems. FA as most population-based algorithm is good at identifying promising area of the search space, but less good at fine-tuning the approximation to the minimization. A novel hybrid firefly algorithm (HFA) based on Rosenbrock’s local search method for constrained numerical and engineering optimization problem that relies on a feasibility-based rule for constraint-handling. Good-point-set method was used to initiate individual position, which strengthened the diversity of global searching. The comparison results with other stochastic optimization algorithms demonstrate that HFA with the embedded local search technique proves to be extremely effective and efficient at locating optimal solutions.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wen Long
AU  - Tiebin Wu
PY  - 2015/08
DA  - 2015/08
TI  - A Hybrid Firefly Algorithm for Constrained optimization and Engineering Application
BT  - Proceedings of the 2015 International Conference on Electronic Science and Automation Control
PB  - Atlantis Press
SP  - 159
EP  - 162
SN  - 2352-538X
UR  - https://doi.org/10.2991/esac-15.2015.40
DO  - 10.2991/esac-15.2015.40
ID  - Long2015/08
ER  -