Abstract
While applying particle swarm optimization to solving traveling salesman problem, some encoding schemes can't utilize well flying character. Particle swarm optimization based on neighborhood encoding for solving traveling salesman problem is put forward in this paper. Scheme of neighborhood encoding makes particles flying efficaciously to interesting region, and eventually makes particle swarm optimization converging with higher efficiency than those utilizing other encoding schemes. Simulation results indicate that new encoding scheme is efficacious.
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.
