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A Study on Compound-Agent and Its Application to the Enterprise Management Information System

Author: FangYuan
Tutor: ShaoShiHuang；GengZhaoFeng
School: Donghua University
Course: Control Theory and Control Engineering
Keywords: Composite AGENT Genetic Algorithms DNA computing MIS Job-shop scheduling Flowshop Scheduling Supply Chain
CLC: TP315
Type: PhD thesis
Year: 2001
Downloads: 420
Quote: 1
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Abstract

This paper summarizes agency body (Agent) and a multi-agency body system (Multi-Agent System) theoretical and applied research on the history and current status, proposed the concept of a composite agent (Compound-Agent). Composite agent is a general multi-agent system development, is a smart combination of distributed and centralized system. General, composite agent as a the body monitoring agent of the Central Command, MA (Monitor-Agent) and execution agent body EA (Execute-Agent) composite composite agent members can also be a composite agent is said compound the agent body can repeatedly composite. Composite agent can easily close collaboration, self-learning and co-evolution with fault diagnosis and recovery capabilities, have higher real-time, fault tolerance and robustness. Can be used to construct a new adaptive capacity, faster reaction speed and higher intelligence system, and better able to adapt to the requirements of a complex dynamic system. Composite agent theory and method of study is divided into several aspects of the structure, function, and collaboration model and learning algorithm, the the composite agents topology structure and MA, the architecture of the EA and function; composite proxy based commitment and the convention forecast Vote Act collaborative model, forecast collaborative model hunt problem object simulation studies; the composite agent learning algorithms, including intensive learning, comprehensive scoring rule base evolution, and made the Simulation Research. Composite agent applied research of its manufacturing enterprise management information system as the background to improve enterprise rapid response capability, competitiveness, maximize profits, to construct a composite agent (EMCA) of enterprise management, and increase the intelligence and agility of enterprise management information system. EMCA's structure and the components of the function, and composite production scheduling and supply chain management agent solutions. Composite-agency body the EMCA to assume the production scheduling problem with intelligent, can complete a variety of modes of production scheduling problem solving, and dynamic adjustment capability. In this paper, the Job-shop based on DNA computing composite agent (JSCA), it bears the Job-shop production scheduling problem solving, which, studies based on the biological mechanism of DNA computing, and applied to practical production planning and scheduling question; established a mathematical model of Job-shop scheduling problem; given of JSCA the structure and composition of the part of the workshop management agent body, the Resource Broker body, the task agent structure, function and achieve; typical 6 × 6 Job -shop scheduling problem given complete scheduling problem using DNA computing methods to obtain a satisfactory result, and according to the optimal solution, data mining, generated ruleset contains 28 rules can be used to rule-based has practical reasoning method of quickly solving similar scheduling problem; the JSCA for solving a woolen mills finishing workshop production scheduling problem, get good results, indicating the Job-shop scheduling problem, use the Job-shop complex agent and feasibility. Flowshop scheduling problems used to solve Flowshop composite agent (FSCA). Flowshop scheduling problem as the goal to minimize processing time and on-time delivery target Flowshop scheduling problem mathematical model depending on the scheduling goals, respectively; given the structure of the FSCA, and for these two types of problems, respectively. gives FSCA realization using conventional genetic algorithm (GA) to solve the problem of production scheduling, rule-based reasoning to achieve collaboration; studied two types of instance Flowshop production scheduling problem, the goal is to minimize processing time Topmaking workshop Spinning workshop production scheduling production scheduling and on-time delivery target has been satisfied with the results, the FSCA dynamic adjustment capability, can be an effective solution to the actual Fl. Yao hop production scheduling problem. Supply chain management is an important part of enterprise management, this paper summarizes the results of part of the supply chain management system research and analysis on the basis of its inadequacies, to build the supply chain composite agent (S CCA) gives the SCCA The structure and function of the various components, a detailed study of SCCA in collaboration implementation. SCCA actually applied to a wool textile enterprises in the supply chain management system and achieved good results. The innovation of this work include the following: 1, proposed the concept of a composite agent, it is the development of the M man S, is the intelligent distribution and concentration of the appropriate combination of the system. A the composite proxy joint commitment and agreement, the voting method, forecast collaboration collaboration model and reinforcement learning, evolution comprehensive scoring rule base learning methods. The combination of the composite agent theory research with modern manufacturing enterprise management theory, to construct composite agent business management, in practical applications, improve enterprise management information system intelligence, agility and adaptability. Based composite agent theory detailed study of the problem of production scheduling and supply chain management issues, and achieved good results in practical application. 4, DNA computing applied to actual production scheduling system can get the Job a sh knock optimal solution for scheduling problems, generate practical scheduling scheme. s, within the framework of the composite agent to achieve large-scale enterprise master production scheduling, the secondary production planning and workshop program integration. Organic integration of static scheduling algorithm with dynamic coordination mechanism, enhance the production scheduling system of intelligence and adaptability of the the actual dynamic production environment.

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