摘要
基于对卸船机调度特征的描述,建立了以最小化卸载作业完成时间为目标的卸船机调度优化模型,设计了混合遗传算法组件以获得问题近似最优解,通过松弛原问题中的难约束,推导了松弛问题的下界并作为原问题的下界.同时,对具有不同规模的问题进行实例计算与分析.结果表明,所设计的混合遗传算法能够在可接受的计算时间内获得合理的解.
Based on the description of scheduling characteristics of ship unloaders, a scheduling optimization model was formulated to minimize the time for unloading operation. The components of a hybrid genetic algorithm were designed to obtain its near optimal solutions. By relaxing the complex constraints of the original problem, a lower bound for the relaxed problem was introduced to be a lower bound for the original problem. Moreover, computational experiments were conducted on instances of different sizes. The computational results show that the developed hybrid genetic algorithm can obtain reasonable solutions within an acceptable computational time.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2012年第9期1431-1435,共5页
Journal of Shanghai Jiaotong University
基金
国家自然科学基金资助项目(51121063)
国家科技支撑计划资助项目(2006BAH02A17)
关键词
卸船机调度
数学规划模型
下界
混合遗传算法
ship unloader scheduling
mathematical programming model
lower bound
hybrid genetic algorithm
