Abstract
Operation scheduling (OS) is a fundamental problem in mapping an application to a computational device. It takes a behavioral application specification and produces a schedule to minimize either the completion time or the computing resources required to meet a given deadline. The OS problem is NP-hard; thus, effective heuristic methods are necessary to provide qualitative solutions. We present novel OS algorithms using the ant colony optimization approach for both timing-constrained scheduling (TCS) and resource-constrained scheduling (RCS) problems. The algorithms use a unique hybrid approach by combining the MAX-MIN ant system metaheuristic with traditional scheduling heuristics. We compiled a comprehensive testing benchmark set from real-world applications in order to verify the effectiveness and efficiency of our proposed algorithms. For TCS, our algorithm achieves better results compared with force-directed scheduling on almost all the testing cases with a maximum 19.5% reduction of the number of resources. For RCS, our algorithm outperforms a number of different list-scheduling heuristics with better stability and generates better results with up to 14.7% improvement. Our algorithms outperform the simulated annealing method for both scheduling problems in terms of quality, computing time, and stability
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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.