Solving the Multi-Objective Shortest Path Problem Based on an Improved Whale Optimization Algorithm

To optimize the solving efficiency of multi-objective path planning problems, this paper proposes an improved solution based on Whale Optimization Algorithm (IDWOA). First, a greedy strategy is adopted to initialize the population, improving the quality of the initial solutions. Second, three novel operators are designed to simulate the hunting behavior of humpback whales, enhancing the global search capability of the algorithm. To validate the performance of IDWOA, experiments are conducted on multiple TSPLIB instances. The experimental results demonstrate that the proposed improvements effectively enhance the algorithm's performance, enabling IDWOA to find better solutions with higher stability