中文摘要：

针对军用补给舰船路径规划问题，需要找出各个配送节点之间的最短路径，用以指导军用补给舰船的调度，提出一种将粒子群优化算法与改进的遗传算法相结合的新方法，规划补给舰船的路径，使其能够快速有效地为战斗舰船配送军用物资。对基本遗传算法进行了改进，然后将其与粒子群算法中相结合，同时利用粒子群算法来对遗传算法的变异方向进行引导，加快了其收敛速度，使得算法的效率和功能得到了很大提高。通过对该改进混合算法求解海战军用物资运输路径优化问题的性能进行仿真，并与自适应遗传算法和免疫遗传算法进行对比分析，验证了提出的算法的优点和有效性。

英文摘要：

Aiming to the problem of military replenishment ships path planning, it needs to find the shortest path between every distribution node to guide the scheduling of military replenishment ships, this paper provides a new method which combined particle swarm algorithm and genetic algorithm to plan the path of replenishment ships, and let them can distribute military supplies for the combat ships quickly and effectively. This paper improves the basic genetic algorithm, and combines it with particle swarm algorithm, and uses particle swarm algorithm to guide the mutation direction of genetic algorithm at the same time. This hybrid algorithm speeds up the convergence, and improves the efficiency and function of the algorithm highly. Through the simulation to the performance of this improved hybrid algorithm of marine military supplies transpor- tation path planning, compares with the self-adapt genetic algorithm and immune genetic algorithm, and analyzes the results, the advantages and effectiveness of the hvbrid algorithm is proved.