Hybrid Algorithms of Multiple Optimization Techniques to Solve Complex Combinatorial Problems
الباحث الأول:
Adel Hashem Nouri
المجلة:
International Journal of Engineering and Information Systems (IJEAIS)
تاريخ النشر:
5 مايو، 2052
مختصر البحث:
This research presents a hybrid method that solves the travelling salesman issue by combining genetic algorithm, local algorithm, and simulated annealing. When tested against a number of benchmarks, this method consistently produced excellent result…
This research presents a hybrid method that solves the travelling salesman issue by combining genetic algorithm, local algorithm, and simulated annealing. When tested against a number of benchmarks, this method consistently produced excellent results. Full hybrid approaches converged to high-quality solutions more quickly, with most seeing substantial gains within the first 10–15 iterations, according to the data. There was an improvement in solution quality of around 15% to 25% over the original solutions. Also, solution time metrics were improved since the total number of iterations needed was lowered. There was less variance in solution quality and the entire hybrid method performed best across all issue situations
