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作 者:邹敢[1] 牛林[1] 刘祥明[1] ZOU Gan;NIU Lin;LIU Xiangming(Faculty of Engineering, Honghe University, Mengzi 661100 , Yunnan, China)
出 处:《河南理工大学学报(自然科学版)》2016年第4期533-538,共6页Journal of Henan Polytechnic University(Natural Science)
基 金:国家自然科学基金资助项目(61463013)
摘 要:针对自动导引车传统集中式作业调度方法存在可靠性差、信息传输效率低和难以应用于大规模系统的问题,提出一种基于多智能体系统(MAS)技术的分布式作业调度方法,详细设计自动导引车系统作业调度问题的MAS模型体系结构、各智能体的行为、协商机制、竞拍值计算等MAS的相关要素,提出允许小车智能体间交换任务和任务智能体有条件重新拍卖的方法来优化调度方案。通过仿真对所提出的方法进行了验证,结果表明,相比传统调度方法,本文提出的方法具有更好的环境适应性、更稳定的综合性能。Since the centralized scheduling approaches, there are some problems, such as poor reliability, low efficiency in information transmission and difficult to apply in large-scale systems, a distributed scheduling approach based on multi-agent system (MAS) technology for automated guided vehicles system (AGVS) was proposed,the related elements of MAS such as the architecture of MAS for AGVS scheduling problem,the agentsb ehaviors, consultation mechanism, bid evaluation were designed carefully. The performance of the approach was improved by allowing vehicle agents exchange jobs and allowing job agent reaction conditionally. The approach based on MAS was compared to more traditional scheduling approaches in an extensive simulation experiment,it is demonstrated that the proposed approach has better environmental adaptability, more stable performance under the different environments.
分 类 号:TP24[自动化与计算机技术—检测技术与自动化装置]
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