Title: Backtracking search algorithm for multi-objective design optimisation

Authors: Ahmed Tchvagha Zeine; Abdelkhalak El Hami; Rachid Ellaia; Emmanuel Pagnacco

Addresses: LMN, INSA-Rouen, National Institute of Applied Sciences of Rouen-France, BP. 08, University Avenue 76801, St Etienne du Rouvray, France; Laboratory of Study and Research in Applied Mathematics, LERMA, Mohammadia School of Engineers, Mohamed V University of Rabat, BP. 765, Ibn Sina Avenue, Agdal, Rabat, Morocco ' LMN, INSA-Rouen, National Institute of Applied Sciences of Rouen-France, BP. 08, University Avenue 76801, St Etienne du Rouvray, France ' Laboratory of Study and Research in Applied Mathematics, LERMA, Mohammadia School of Engineers, Mohamed V University of Rabat, BP. 765, Ibn Sina Avenue, Agdal, Rabat, Morocco ' LMN, INSA-Rouen, National Institute of Applied Sciences of Rouen-France, BP. 08, University Avenue 76801, St Etienne du Rouvray, France

Abstract: In engineering, design problems are generally multi-objective with complex non-linear constraints. Therefore, the computing effort can often rise significantly with the number of objectives and constraints' evaluation. The metaheuristics algorithms are nowadays considered as powerful algorithms to deal with multi-objective optimisation problems. In this article, we develop a new backtracking search algorithm for multi-objective optimisation, called BSAMO, to solve this kind of problems. It is evaluated here through a set of benchmarks problems and two structural design applications. BSAMO's numerical results are compared with those of NSGA-II by two performance measures. They show that the proposed algorithm is able to produce a better convergence towards the Pareto front and to preserve the diversity of the solutions.

Keywords: backtracking search; design optimisation; evolutionary algorithms; multi-objective optimisation; structural optimisation.

DOI: 10.1504/IJMMNO.2017.086793

International Journal of Mathematical Modelling and Numerical Optimisation, 2017 Vol.8 No.2, pp.93 - 107

Received: 16 Aug 2016
Accepted: 03 Mar 2017

Published online: 13 Sep 2017 *

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