摘要
针对海上溢油事故应急物资调度问题,本文考虑事故需求点受海上风浪影响而发生漂移的特点,分析需求点漂移对救援路径规划和环境损失的影响,构建以运输成本和环境损失最小为优化目标的数学模型,提出一种改进的遗传模拟退火混合算法。以蓬莱石油泄露事故的实际数据为背景,对模型进行实例验证和算例分析。结果显示:与不考虑需求点漂移获得的救援方案相比,本文方法在总航行距离上减少了9.11%、环境污染降低了41.17%,说明海上溢油应急救援调度问题中考虑需求点漂移的重要性;针对不同规模、不同需求点分布的算例,本文方法在算法优越性和求解稳定性上均体现出较为明显的优势,表明本文方法可以获得较优的调度方案,实现更准确高效的应急救援;通过灵敏度分析获知,提升船舶容量可以明显降低应急救援运输成本,且提升船舶航行速度可以更好地降低环境污染。
This paper focuses on the emergency material scheduling for oil spill accident andanalyzesthe impact of demand point drift on rescue path planning and environmental lossconsidering the accident demand point changes caused by sea wind and waves.The optimization model is developed to minimizetransportation cost and environmental loss,and an improved hybrid genetic simulated annealing algorithm is used to solve the model.Based on the actual data of Penglai oil spill accident,the study verifies the model effectiveness through thecase study and numerical examples.The results show that compared with the rescue scheme obtained without considering the demand point drift,the proposed method reduces the total sailing distance by 9.11%and reduces the environmental pollution by 41.17%.The proposed method shows obvious advantages in algorithm superiority and solution stability with different scale and distribution of demand pointsThe sensitivity analysis also shows that increasing the ship capacity can significantly reduce the emergency rescue transportation cost,and increasing the ship speed is helpful toreduce the environmental pollution.
作者
张昊
陶宁蓉
杨男
ZHANG Hao;TAO Ning-rong;YANG Nan(College of Engineering Science and Technology,Shanghai Ocean University,Shanghai 201306,China;Shanghai Engineering Research Center of Marine Renewable Energy,Shanghai 201306,China)
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2022年第6期269-280,共12页
Journal of Transportation Systems Engineering and Information Technology
基金
国家自然科学基金(71501125)
上海市科学技术委员会资助项目(19DZ2254800)。
关键词
水路运输
应急物资调度
遗传模拟退火混合算法
海上溢油
需求点漂移
waterway transportation
emergency material scheduling
hybrid genetic and simulated annealing algorithm
offshore oil spill
demand point drift
