运筹学
地铁列车时刻表
容器(类型理论)
选择(遗传算法)
解算器
收入
计算机科学
粒子群优化
运输工程
业务
工程类
操作系统
机器学习
会计
人工智能
程序设计语言
机械工程
作者
Jian Du,Nuan Wu,Xu Zhao,Jun Wang,Liming Guo
标识
DOI:10.1080/03088839.2022.2160499
摘要
The liner shipping schedules determine the container transportation time and the arrival time of ships, which has a significant influence on the shipper selection behavior and the transportation demand. This paper addresses the container liner shipping schedule optimization with shipper selection behavior considered. Our problem is formulated as a mixed-integer nonlinear programming model, where the shipper selection behavior is evaluated by a nested logit model. A particle swarm optimization (PSO) framework embedded with CPLEX solver is designed, by combining the constraint relaxations and the linearization techniques with the heuristic rules. The numerical experiments are conducted based on the Persian Gulf route of COSCO SHIPPING LINES. The results show that: the total freight demand is increased by 23% and the weekly operation revenue is increased by 31% after considering shipper selection. Besides, we find that the planned ship speed should be increased for time-preference shippers with electronic or refrigerated products, while it should be decreased for price-preference shippers with general or bulk cargoes. These conclusions can provide decision support for the operation practice of liner shipping schedule design.
科研通智能强力驱动
Strongly Powered by AbleSci AI