Abstract
A hyper-heuristic is a high-level method that manages a set of low-level heuristics to solve various problems in a problem-independent manner. In this paper, we propose a new selection hyper-heuristic with the multilevel paradigm. The multilevel paradigm refers to the process of dividing large problems into sub-problems. Each sub-problem is being solved to reach an optimal solution by using the resulting solution from a previous level as a starting solution at the next level. The selection strategy chooses the adequate low-level heuristic at any iteration during the search. For analysis purposes, several variants of hyper-heuristics are implemented and Max-SAT is used as the test bed. The experimental results revealed that the multilevel paradigm together with a new hybrid-heuristic selection mechanism provides a substantial performance improvement. A comparison with two known state of the art algorithms that are GSAT and WALKSAT is given to further show the efficiency of our method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
