Abstract
Continuous ant-colony optimization is an emerging field in numerical optimization, which tries to cope with the optimization challenges arising in modern real-world engineering and scientific domains. One of them is large-scale continuous optimization problem that becomes especially important for the development of recent emerging fields like bio-computing, data mining and production planing. Ant-colony optimization (ACO) is known for its efficiency in solving combinatorial optimization problems. However, its application to real-parameter optimizations appears more challenging, since the pheromone-laying method is not straightforward. In the recent year, there have been developed a several adaptations of the ACO algorithm for continuous optimization. Among them the Continuous Differential Ant-Stigmergy Algorithm (CDASA) arises as promising method for global continuous large-scale optimization. In this paper we address a systematic performance evaluation of CDASA on a predefined test suite and experimental procedure provided for the Competition on Real-Parameter Single Objective Optimization at CEC-2013.
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.
