摘要
港口调度优化问题分为离散的泊位分配和时变的岸桥调度问题,并构建泊位-岸桥联合调度优化模型。对于到港船舶泊位分配问题,提出靠泊优先权概念,并以此作为基因编码基础。岸桥分配中提出岸桥调度的公平分配原则,使得岸桥分配存在初始分配和最终分配。为解决非线性混合整数规划模型,改进了遗传算法,模型目标是使所有船舶在港总时间最小。实验算例验证了算法设计的优越性。
The operation of container terminals is divided into discrete berth allocation and time-variant scheduling of quay cranes. A joint scheduling model is then developed for the container berth-quay crane optimization. For berth allocation, the concept of berth priority was proposed to allocate berths for arriving ships,which is the basic unit in the coding system. A fair allocation principle was also designed in the scheduling of quay cranes, which makes the allocation into initial and final allocations. To solve this nonlinear mixed-integer programming model, the genetic algorithm was improved with the goal of minimizing the total time of all the ships in port. Computational experiments show the performance improvement of the proposed algorithm.
出处
《工业工程与管理》
CSSCI
北大核心
2017年第2期60-68,共9页
Industrial Engineering and Management
基金
国家自然科学基金资助项目(71302052,71673181)
上海市浦江人才计划资助项目(14PJC070)
关键词
泊位一岸桥调度
优先权
公平原则
非线性混合整数规划模型
遗传算法
berth and crane scheduling
priority
fair principle
nonlinear mixed integer programming model
genetic algorithm
