摘要
动态连续泊位分配问题已被许多文献研究过,多数研究都是设计专门的启发式算法求解该问题。基于约束规划的视角,提出了一个新的约束规划模型,该模型是以所谓的区间变量为中心设计的,将船舶装卸活动和靠泊位置都建模为区间变量,使得模型表达自然简洁。在共同的基准测试实例上进行小规模和大规模数值实验,结果显示约束规划方法求解动态连续泊位分配问题的性能超过现有文献中的贪婪随机适应性搜索算法和随机约束搜索算法。
The dynamic and continuous Berth Allocation Problem （BAP） is studied to minimize the total weighted flow time. Most previous studies designed specific heuristic algorithms to solve the BAP. This research tackles the BAP from a constraint programming （CP） perspective. A concise CP model for the BAP is proposed, which is designed around so-called interval variables. Container ships＇ handling activities and berthing positions are all modeled with interval variables. Both small and large scale numerical experiments are carried out to test the performance of the CP model. The results of CP are compared with other algorithms presented in the literature, i. e., greedy randomized adaptive search algorithm and stochastic beam search algorithm. The results show that the CP method is more effective to solve the BAP.
出处
《工业工程与管理》
CSSCI
北大核心
2013年第6期27-31,共5页
Industrial Engineering and Management
基金
国家自然科学基金资助项目(71172076)
交通部应用基础研究资助项目(2011-329-810-450)
上海市科委地方院校专项资助项目(11510501800)
上海市教委科研创新资助项目(11YZ135)
上海市重点学科建设资助项目(S30601)
关键词
集装箱码头
泊位分配
约束规划
container terminal
berth allocation
constraint programming
