关键词: 水路运输, 效率和油耗优化, 深度Q网络, 进港船舶, 双种群协作框架

Abstract: To address the significant differences in fuel consumption among various types of vessels during port entry and the challenge of balancing scheduling efficiency with energy optimization, this study investigates a coordinated optimization approach for port entry efficiency and fuel consumption considering the heterogeneity in fuel efficiency. A bi-objective mixed-integer nonlinear programming model is formulated to minimize the total port entry time and the overall fuel consumption of vessels. To solve the model effectively, a cooperative meta-heuristic algorithm driven by a Deep Q-Network (DQN) is proposed. The algorithm incorporates an improved Nawaz-Enscore-Ham (NEH) heuristic to generate initial scheduling sequences and designs a DQN-based dual-population cooperative search framework to adjust vessel entry sequences and speed profiles dynamically. Using a representative scheduling scenario from Tianjin Port, numerical experiments are conducted to validate the performance of the proposed method. The results demonstrate that the DQN-driven cooperative meta-heuristic algorithm outperforms traditional heuristic methods in terms of solution quality and distribution within the objective space. Compared to the commercial solver CPLEX, the proposed algorithm achieves exponential improvements in computational efficiency while maintaining the overall deviation of the two objectives within a range of 2.04% to 12.82%, yielding consistently high-quality approximate solutions. Further comparative analysis reveals that incorporating heterogeneous fuel efficiency significantly alters the scheduling priorities of vessels, underscoring the critical impact of energy consumption structure on port entry organization strategies.

Key words: waterway transportation, efficiency and fuel consumption optimization, deep Q-network, port-arriving ships, bi population cooperative framework