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为提高自动化集装箱码头堆场的作业效率,针对堆场同一箱区的两端作业(堆存或取出),考虑双起重机时空同步约束条件,以最小化作业总完成时间为目标,建立双起重机调度混合整数规划模型,确定起重机在每个时间点上所处贝位及其作业状态(移动或装卸),设计遗传算法对大规模任务数量问题进行求解.算例分析结果表明,在大规模问题上,GA在解的质量上逐渐优于CPLEX算法,且运算时间远小于CPLEX,证明了该双起重机调度模型与算法的有效性及合理性.
In order to improve the operation efficiency of automated container terminal yard, aiming at the task of both ends (stacking or taking out) in the same box area of yard and considering the space-time synchronization constraints of double cranes, aiming to minimize the total completion time of work, Mixed integer programming model to determine the crane at each point in the berth and its operating status (moving or loading and unloading), the design of genetic algorithms to solve the problem of large-scale tasks.Example analysis results show that in the large-scale problems , GA is better than CPLEX algorithm in terms of the quality of solution, and the computation time is far less than that of CPLEX, which proves the validity and rationality of this two-crane scheduling model and algorithm.