Abstract
Path relinking is a population-based heuristic that explores the trajectories in decision space between two elite solutions. It has been successfully used as a key component of several multi-objective optimizers, especially for solving bi-objective problems. In this paper, we focus on the behavior of pure path relinking, propose several variants of the path relinking that vary on their selection strategies, and analyze its performance using several many-objective NK-landscapes as instances. The study shows that the path relinking becomes more effective in improving the convergence of the algorithm as the number of objectives increases. It also shows that the selection strategy associated to path relinking plays an important role to emphasize either convergence or spread of the algorithm.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.