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自动化立体车库管理系统的设计(英文文献+CAD图纸) 第4页

更新时间:2010-4-3:  来源:毕业论文
自动化立体车库管理系统的研究(英文文献+CAD图纸)
Fig. 2. Functional modules and relationships of a fractal in an FrMS.

transmit composite information to correspondent fractals. The function of an analyzer is to analyze alternative job profiles with status information, to rate dispatching rules, and to simulate analyzed job profiles in real-time. The analyzer finally reports results to the resolver so that the resolver can use them to make decisions. A resolver plays the most important role in a fractal, generating job profiles, goal-formation processes, and decision-making processes. During goal-formation processes, the resolver may employ a variety of numerical optimization or heuristic techniques to optimize the fractal’s goal. If necessary, the resolver executes negotiations, cooperation, and coordination among fractals. The function of an organizer is to manage the fractal status and fractal addresses, particularly for dynamic restructuring processes. The organizer may use numerical optimization techniques to find an optimal configuration while reconfiguring fractals. The fractal status is used to select the best job profile among several alternatives, and the fractal address is used to find the physical address of the fractal (e.g. machine_name, port_number, etc.) on the network. The function of a reporter is to report results from all processes in a fractal to others. In the case of a bottom-level controller, the fractal is similar to a traditional equipment controller. Therefore, most of its messages are commands for controlling the hardware.
2.2. Agents in an FrMS    
Agent technology has been widely used for various applications including information filtering and gathering [16], knowledge management [17], supply chain management [18], manufacturing architecture, system and design [19–21]. While the features and characteristics of an agent vary depending on the application, some common features found across different applications are as follows: Autonomy: capability of controlling and acting for itself in order to achieve goals. Mobility: capability of migrating its location to other places (an agent with mobility is called a mobile agent, otherwise known as a software or stationary agent). Intelligence: capability of learning and solving problems. Cooperativeness: capability of helping others if requested and accepting helps from others. Adaptability: capability of being effectively used at various domains. Reliability: capability of dealing with unknown situations (disturbances) and continuing actions if committed, etc. The mobility of agents is a useful feature in a distributed and dynamic system. A mobile agent is not bound to the system where it begins execution. It can travel freely among the controllers in a network and transport itself from one system in a network to another. The following are some advantages of the use of mobile agents in a system [22]: (1) it reduces the network load, (2) it overcomes network latency, (3) it encapsulates protocols, (4) it executes asynchronously and autonomously, (5) it adapts dynamically, (6) it is naturally heterogeneous, and (7) it is robust and faulttolerant. The types and functions of agents that implement functional modules of an FrMS have been brie?y described, and their initial development has been published in the earlier literature [11]. This paper enhances and re?nes the previously defined types  and functions of agents so that they can perform functions of fractals successfully in the system. The names, types, and functions of agents in the FrMS are described as follows. The terms ‘‘-M’’ and ‘‘-S’’ written after the abbreviated name of each agent represent mobile agents and software agents, respectively.
2.2.1. Agents for an observer
Network monitoring agent (NMA-S): It monitors messages from other fractals through TCP/IP. It receives messages from the upper/same/lower-level fractals, such as requests for negotiations, negotiation replies, job orders, status information, etc. The NMA delivers those messages to the resolver or the analyzer. Equipment monitoring agent (EMA-S): It monitors messages directly coming from equipment through a serial communication protocol such as RS232/ 422. Information on the status of equipment including signals indicating the start and completion of jobs are detected by the EMA. However, the fractal need not directly control equipment if it is not included in a bottom-level.
2.2.2. Agents for an analyzer
Schedule evaluation agent (SEA-S): A SEA evaluates job profiles generated by the resolver. It helps the resolver to select the best job profile with respect to the current situation of the fractal. Dispatching-rule rating agent (DRA-S): It chooses the best dispatching rule for achieving its goals among several rules, such as shortest processing time (SPT), earliest due date (EDD), and so on. Real-time simulation agent (RSA-S): It performs real-time simulations in the on-line state with the results of the analyzed job profiles and the best dispatching rule. The RSA reports the results of simulations to the resolver.

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