An improved hybrid biogeography-based optimization algorithm for constrained optimization problems

DOI

10.2991/ic3me-15.2015.138How to use a DOI?

Keywords

optimization algorithm, Constrained optimization problems

Abstract

Constrained optimization problems are very important as they are encountered in many science and engineering applications. A hybrid method based on modified augmented Lagrangian multiplier and biogeography-based optimization (BBO) algorithm is proposed to solve constrained optimization problems. The basic steps of the proposed method are comprised of an outer iteration, in which the Lagrangian multipliers and various penalty parameters are updated using a first-order update scheme, and an inner iteration, in which a nonlinear optimization of the modified augmented Lagrangian function with simple bound constraints is implemented by BBO algorithm. Numerical results show that the proposed method is reliable and efficient for solving constrained optimization problems.

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  - Ximing Liang
AU  - Songjin Xu
PY  - 2015/08
DA  - 2015/08
TI  - An improved hybrid biogeography-based optimization algorithm for constrained optimization problems
BT  - Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
PB  - Atlantis Press
SP  - 710
EP  - 714
SN  - 2352-5401
UR  - https://doi.org/10.2991/ic3me-15.2015.138
DO  - 10.2991/ic3me-15.2015.138
ID  - Long2015/08
ER  -