Research Repository

A multiobjective optimization based framework to balance the global exploration and local exploitation in expensive optimization

Feng, Z and Zhang, Q and Zhang, Q and Tang, Q and Yang, T and Ma, Y (2015) 'A multiobjective optimization based framework to balance the global exploration and local exploitation in expensive optimization.' Journal of Global Optimization, 61 (4). 677 - 694. ISSN 0925-5001

Full text not available from this repository.

Abstract

© 2014, Springer Science+Business Media New York. In many engineering optimization problems, objective function evaluations can be extremely computationally expensive. The effective global optimization (EGO) is a widely used approach for expensive optimization. Balance between global exploration and local exploitation is a very important issue in designing EGO-like algorithms. This paper proposes a multiobjective optimization based EGO (EGO-MO) for addressing this issue. In EGO-MO, a global surrogate model for the objective function is firstly constructed using some initial database of designs. Then, a multiobjective optimization problem (MOP) is formulated, in which two objectives measure the global exploration and local exploitation. At each generation, the multiobjective evolutionary algorithm based on decomposition is used for solving the MOP. Several solutions selected from the obtained Pareto front are evaluated. In such a way, it can generate multiple test solutions simultaneously to take the advantage of parallel computing and reduce the computational time. Numerical experiments on a suite of test problems have shown that EGO-MO outperforms EGO in terms of iteration numbers.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 09 Jul 2015 13:32
Last Modified: 17 Oct 2019 14:15
URI: http://repository.essex.ac.uk/id/eprint/14051

Actions (login required)

View Item View Item