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Smart Solution for STSP Semantic Traveling Salesman Problem via Hybrid Ant Colony System with Genetic Algorithm

Travelling Salesman Problem (TSP) is one of the main and famous problems in finding the shortest path. But life is not ideal, so in this paper, we proposed design a Semantic Travelling Salesman Problems (STSP). The STSP enhances nodes by suitable Ontologies according to a real problem to be more flexible. Also, we proposed a hybrid model (ACSGA) combining the ant colony system (ACS) with the genetic algorithm (GA). That is to speed-up convergence and finds an effective path of a Semantic Travelling Salesman Problem STSP. The performance of the proposed hybrid model ACSGA was faster by 66% than other standard algorithms. And the distance decreases by 0.72%. We apply the proposed solution to the real problem with challenges as traffic overcrowding and weather changeable. So, the proposed STSP in this paper used traffics and weather Ontology as a case study. The proposed method modified the results according to time which decreases by 2.3%.