摘要
随着集装箱船舶大型化的发展趋势,越来越多的班轮公司积极建设轴幅式集装箱海运网络来提高服务效率、降低单位运营成本。为此,建立非线性轴幅式集装箱海运网络优化模型,以集装箱海运网络总成本最小为目标,考虑港口通过能力约束,应用Q-学习方法与混沌优化方法结合的混合优化算法求解,寻找合理的集装箱运输路径,配置适宜的集装箱船舶。算例结果表明:混合优化算法可以有效地求解海运集装箱运输路径优化与船舶配置问题;轴幅式网络比直达运输可节省10%的运输成本。
With the developing trend of larger container ships,hub-and-spoke container shipping network was established by more and more liner shipping companies to improve the service efficiency and reduce the unit operation cost. Therefore,a non-linear hub-and-spoke container shipping network optimization model considering the port throughput capacity was proposed. The purpose of the proposed model was to minimize the total cost of container shipping network. Then,a hybrid optimization algorithm combining Q-learning method with chaos optimization algorithm was used to solve the problem of reasonable container shipping route and suitable ship deployment. A case study was carried out to assess the effectiveness of the proposed model. The results show that the hybrid optimization algorithm can efficiently solve the problem of container shipping route optimization and ship deployment. Besides,comparing with the direct transportation,the transportation cost of the hub-and-spoke network can be reduced by 10%.
出处
《重庆交通大学学报（自然科学版）》
CAS
北大核心
2018年第1期109-115,共7页
Journal of Chongqing Jiaotong University(Natural Science)
基金
国家自然科学基金项目(51309049
51279026)
关键词
交通运输工程
集装箱港口
轴幅式网络
运输路径
混合优化
traffic and transportation engineering
container terminal
hub-and-spoke network
shipping route
hybrid optimization
