Abstract
To improve the performance of intelligence optimization algorithm for solving Job Shop Scheduling Problem ,a hybrid ant colony algorithm called tabu search and ant (TSANT) algorithm with global convergence was proposed. In the hybrid ant colony algorithm, the MMAS algorithm was applied to search in the global solution space, and the tabu search algorithm was utilized as the local algorithm. The global convergence of TSANT algorithm proved to be true by analyzing the convergence of MMAS algorithm and TS algorithm by Markov chain theory. Under the guidance of the above convergence theory, we applied the hybrid algorithm to some typical benchmarks problems and found out the optimums of problems FT10, LA25and LA39 in a short period, which improved the quality of the solutions of Job Shop Scheduling Problem and demonstrated the effectiveness of the hybrid ant colony algorithm both in theory and practice.
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.
