The directed search method for multi-objective memetic algorithms

We propose a new iterative search procedure for the numerical treatment of unconstrained multi-objective optimization problems (MOPs) which steers the search along a predefined direction given in objective space. Based on this ideawewill present twomethods: directed search (DS) descent which seeks for improvements of the given model, and a novel continuation method (DS continuation) which allows to search along the Pareto set of a given MOP. One advantage of both methods is that they can be realized with and without gradient information, and if neighborhood information is available the computation of the search direction comes even for free. The latter makes our algorithms interesting candidates for local search engines within memetic strategies. Further, the approach can be used to gain some interesting insights into the nature of multi-objective stochastic local search which may explain one facet of the B Oliver Schütze [email protected] Adanay Martín [email protected] Adriana Lara [email protected] Sergio Alvarado [email protected] Eduardo Salinas [email protected] Carlos A. Coello Coello [email protected] 1 Cinvestav-IPN, Computer Science Department, Av. IPN 2508, Col. San Pedro Zacatenco, C. P. 07360 Mexico, Mexico 2 Mathematics Department, ESFM-IPN, Edificio 9, UPALM, Mexico, Mexico