An Optimized Discrete Dragonfly Algorithm Tackling the Low Exploitation Problem for Solving TSP

Optimization problems are prevalent in almost all areas and hence optimization algorithms crucial for a myriad of real-world applications. Deterministic tend to be computationally costly time-consuming. Hence, heuristic metaheuristic more favoured as they provide near-optimal solutions an acceptable amount time. Swarm intelligence being increasingly used owing their simplicity good performance. The Dragonfly Algorithm (DA) is one which inspired by the swarming behaviours dragonflies, it has been proven have superior performance than other multiple worth considering its application traveling salesman problem predominant discrete problem. original DA only suitable solving continuous and, although there binary version algorithm, not easily adapted like TSP. We previously proposed algorithm However, low effectiveness, large TSP problems. In this paper, we propose optimized using steepest ascent hill climbing local search. applied modelling package delivery system Kuala Lumpur area benchmark problems, found higher effectiveness some swarm algorithms. It also efficiency DA.