CAJ | 학술논문

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。
침대군용보급함선로경규화문제，수요조출각개배송절점지간적최단로경，용이지도군용보급함선적조도，제출일충장입자군우화산법여개진적유전산법상결합적신방법，규화보급함선적로경，사기능구쾌속유효지위전두함선배송군용물자。대기본유전산법진행료개진，연후장기여입자군산법중상결합，동시이용입자군산법래대유전산법적변이방향진행인도，가쾌료기수렴속도，사득산법적효솔화공능득도료흔대제고。통과대해개진혼합산법구해해전군용물자운수로경우화문제적성능진행방진，병여자괄응유전산법화면역유전산법진행대비분석，험증료제출적산법적우점화유효성。
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 hybrid algorithm is proved.