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摘要: 平行系统是一种建立在人工社会和计算实验基础上的科学研究方法，它的特点是既能真实反映现实系统的动态过程，又能实时优化现实系统的控制过程.自动化集装箱码头是一类典型的复杂系统，既存在不计其数的作业方案，同时也有大量的约束条件.如何在最短时间和最低能源消耗的前提下，完成具有间歇和批次特征的集装箱转运任务，是涉及到数学、控制、管理和计算机等多个学科的重大课题.本文采用数据引擎作为人工社会中的基本计算单元，构成一个复杂的平行系统，用于自动化集装箱码头信息控制系统的研究.数据引擎作为一种面向图形化元件组态的计算环境，非常适用于复杂系统的建模与计算.在可视化和动态重构技术的支持下，利用380个数据引擎对一个具有8台岸桥、25辆AGV和16台龙门吊组成的港机系统进行了自动化作业过程的计算实验.研究结果表明，数据引擎技术是实现平行系统的有效方法，由多数据引擎组成的计算环境，能够大幅度降低自动化集装箱码头信息控制系统建模的复杂程度，能够将码头系统的管理和控制过程无缝地融合在一起.该平行系统可直接与港机设备对接，建立“人工码头”和“物理码头”之间的平行关系，从而实现对港机设备的最优控制.Abstract: Parallel systems are a kind of scientific research method based on artificial society and computational experiments, which can not only reflect the dynamic process of real system but also optimize the control process of the real system in real time. The automatic container terminal is a typical complex system having numerous operating schemes and a large number of constraints. How to accomplish the container transport task with intermittent and batch features while using minimum time and energy consumption is a major issue, which involves many disciplines such as mathematics, control, management and computer. In this paper, the data engine is used as the basic computing unit of the artificial society of parallel systems, to study the information control system of the container terminal. As a computing environment for graphical configuration, the data engine is ideal for modeling and computation of complex systems. With the support of the visualization and dynamic reconfiguration technologies, 380 data engines are used to perform computational experiments on the automation process of a port system, which consists of 8 bridge cranes, 25 AGVs and 16 gantry cranes. The results indicate the effectiveness of the data engine technology for parallel systems, and the computing environment composed of multiple data engines can greatly reduce the modeling complexity of the port information control system as well as make the information management work with the control process cooperatively. The proposed parallel systems can connect to port devices directly to establish a parallel relationship between "artificial container terminal" and "physical container terminal" so as to achieve the optimal control of the port devices.
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Key words:
- Parallel system /
- automatic container terminal /
- data engine /
- complex system /
- multi-agents
1) 本文责任编委 魏庆来 -
图 6 卸船模型的应用实例: AGV代理与车道代理的动态交互
Fig. 6 An application example of the discharge model: The dynamic interaction among AGV agents and lane agents
图 12 平行码头中人机交互系统工程应用实例
Fig. 12 An application example of PCTICS human-computer interaction system
表 1 不同行驶策略下AGV的任务时耗(s) $^{1}$
Table 1 The time cost of AGV task under different driving strategies (s) $^{1}$
$T_{\rm mode 1}$ $T'_{\rm mode 1}$ $T_{\rm mode 2}$ $T'_{\rm mode 2}$ (Task 1) (Task 2) (Task 1) (Task 2) 251 316 243 328 267 320 245 315 284 330 253 301 256 349 254 322 257 328 253 327 432 334 260 320 526 328 261 457 468 304 248 533 318 323 265 450 241 323 276 322 $^{1}$Task 1表示从104号岸桥搬运10个集装箱至47号堆场, Task 2表示从105号岸桥搬运10个集装箱至49号堆场; $T_{\rm mode 1}$和$T'_{\rm mode 1}$分别表示无汇流行驶策略下AGV完成任务1和任务2的时耗; $T_{\rm mode 2}$和$T'_{\rm mode 2}$分别表示汇流行驶策略下AGV完成任务1和任务2的时耗. 
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