A Novel Discrete Zebra Optimization Algorithm for Traveling Salesman Problem

The Traveling Salesman Problem is a classic optimization challenge used to benchmark meta-heuristic algorithms. This paper introduces a novel approach, the Discrete Zebra Optimization Algorithm (DZOA), specifically tailored for TSP. Inspired by the foraging behavior of zebras, the Zebra Optimization Algorithm (ZOA) has shown promise in continuous optimization. However, its application to discrete problems like TSP has been unexplored until now. DZOA addresses this gap by combining a discrete version of ZOA with two innovative neighborhood search strategies. This hybrid approach enables effective exploration of the TSP's discrete solution space. To evaluate DZOA's performance, we applied it to ۱۰ standard TSP instances from TSPLIB. Our results demonstrate that DZOA significantly outperforms existing metaheuristic methods in both solution quality and computational efficiency.

کلیدواژه ها:

discrete zebra optimization algorithm ، traveling salesman problem ، neighborhood search strategies