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.
For improving the stack yard operating efficiency at ACT, focused on both side operations( storage or retrieval) for the single container block in stack yard,a mixed-integer programming model was proposed to minimize the total operating time,and determine the crane movement and work status( moving or handling) by considering the time and space synchronization constraints of twin crane parallel operation. A genetic algorithm was developed to quickly solve the near-optimal solutions for large scale problem. Practical examples result show that, for large scale problem, the solution quality by GA is gradually better than CPLEX's,and the operation time is far less,which proves the validity and rationality of model and algorithm for scheduling twin synchronized stacking cranes.