Abstract
An adaptive parallel ant colony optimisation (PACO) algorithm on massively parallel processors (MPPs) is presented. In the algorithm, we propose a strategy for information exchange between processors that makes each processor choose a partner to communicate with and update their pheromone adaptively. We also propose a method of adaptively adjusting the time interval for the exchange of information according to the diversity of the solutions, to increase the quality of the optimisation results and to avoid early convergence. The analysis and proof of the convergence of the PACO algorithm is presented. Experimental results of the TSP confirm our theoretical conclusions and show that our PACO algorithm has a high convergence speed, high speedup and high efficiency.
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.
