Abstract
Multi-objective optimization is an NP-hard problem. ADSE (automatic design space exploration) using heuristics has been proved to be an appropriate method in resolving this problem. This paper presents a hyper-heuristic technique to solve the DSE issue in computer architecture. Two algorithms are proposed. A hyper-heuristic layer has been added to the FADSE (framework for automatic design space exploration) and relevant algorithms have been implemented. The benefits of already existing multi-objective algorithms have been joined in order to strengthen the proposed algorithms. The proposed algorithms, namely RRSNS (round-robin scheduling NSGA-II and SPEA2) and RSNS (random scheduling NSGA-II and SPEA2) have been evaluated for the ADSE problem. The results have been compared with NSGA-II and SPEA2 algorithms. Results show that the proposed methodologies give competitive outcomes in comparison with NSGA-II and SPEA2.
Highlights
IntroductionThe optimization of multiple objectives becomes harder too
Computer architectures are getting more complex day by day
Simple random selection hyper-heuristic method has been used. This hyper-heuristic method is quite dominant in the field because of its execution according to the circumstances
Summary
The optimization of multiple objectives becomes harder too. This occurs because usually the objectives are contradictory to each other. Simple random selection hyper-heuristic method has been used This hyper-heuristic method is quite dominant in the field because of its execution according to the circumstances. This heuristic type uses existing heuristic methods [1]. There are two modules of the traditional selection hyper-heuristic model [2]. These include low level heuristics selection and acceptance. To the best of our knowledge, the literature is relatively poor in the application of selection hyper-heuristics in the ADSE field using the FADSE tool
Sign-in/Register to view highlights & summary 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 callMore From: Engineering, Technology & Applied Science Research
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.
