CAJ | 학술논문

泊位分配是提高港口运营效率的关键。针对群岛泊位分配问题，以船舶总在港时间为优化目标，构建了群岛泊位分配问题模型，并提出了一种混合粒子群算法进行求解。该算法在更新粒子状态时加入模拟退火和免疫调节操作，增强了算法的全局搜索能力。实验结果表明，混合粒子群算法在求解群岛泊位分配问题时，具有较好的优化性能，验证了算法的有效性和可行性。
박위분배시제고항구운영효솔적관건。침대군도박위분배문제，이선박총재항시간위우화목표，구건료군도박위분배문제모형，병제출료일충혼합입자군산법진행구해。해산법재경신입자상태시가입모의퇴화화면역조절조작，증강료산법적전국수색능력。실험결과표명，혼합입자군산법재구해군도박위분배문제시，구유교호적우화성능，험증료산법적유효성화가행성。
Berth allocation is the key to improving the efficiency of port operation .Aiming at the archipel-ago berth allocation, a model is established with minimum waiting time of ships as objective , and a hybrid particle swarm optimization ( HPSO) algorithm proposed .In HPSO, simulated annealing ( GA) and artifi-cial immunity ( AI) are applied to update the state of particles , thus improving the global optimization of HPSO.Numerical experiment results show that , the HPSO is an effective and feasible algorithm for solving the archipelago berth allocation problem .