Seyahat satışı sorununun çözümü için değiştirilmiş toptan optimizasyon algoritmasının kullanılması

In e study the most well-known issues related optical fibre network, which are still viewed as a challenge for various networks. Depending on current optimization techniques, the Travel Sellers (TSP) problem is one of the oldest approaches to solving this kind of problem.Best andefficient approachto solve animal-based TSPproblem is by using modified algorithms. It was created for the difficulty of the travelling salesman. The programme used a set of traditional datasets with a 51 to 150 range. Theresults showthat the hybrid algorithm (WOA+NN) outperformsAS(Ant system), WOA,GA,andSA for50%of all datasets.Ant System(AS)is the second most effective algorithm when compared to meta-inference techniques for 40% of all data sets. A better number, worse number, mean, standard deviation, and mean CPU time solutions are also shown in the full analysis with regard to meta-inference. The whale Improvement Algorithm (WOA) has a performance rate of over 50% in discovering the best solutions, according to metrics. The Ant System (AS) outperforms all optimal solutions by 40%. Finally, compared to previous algorithms for medium-sized data sets, the Whale Improvement Algorithm (WOA) solves the discrete problemin aReasonable amount of time.The study concentrates on TSPLIB-type issues with the WhaleImprovement Algorithm (WOA) and Genetic Algorithm(GA).