Abstract
Abstract The traveling salesman problem (TSP) is one of typical combinatorial optimization problems. Ant colony optimization (ACO) is an effective method to solve the traveling salesman problem, but there are some non-negligible shortcomings hidden in the original algorithm. The primary objective of this research is to optimize the ACO to produce quality work throughout solving TSP. To this end, the hybrid SOS-MMAS algorithm is proposed. Concretely, apply the advanced Max-Min Ant System (MMAS) as the basic algorithm to raise task scheduling efficiency, meanwhile introduce symbiotic organisms search (SOS) into the MMAS to optimize the key parameters. Experiments were carried out on typical TSP instances of different scales, and the SOS-ACO and ACO algorithms were compared with SOS-MMAS, which proved the excellent performance of SOS-MMAS in solving TSP. Rationality of the algorithm design and high performance has been illuminated by experimentation. In addition, the model also could serve to suggest further research of TSP or other related areas.
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.
