重大工程多主体协同合作利益分配及创新激励机制研究

针对重大工程供应链中多主体协同合作利益分配以及创新决策问题，考虑到两阶段博弈中决策的不同情形，应用非合作-合作混合的双体博弈方法进行了研究。通过模型构建与求解得到各主体的最优创新努力、收益以及整个系统的最优收益，并在此基础上拓展模型，分析成本补贴和垂直整合两种激励机制对各主体最优创新努力、收益和供应链系统收益的影响。研究发现：重大工程多主体协同合作中存在创新投入不足的情况，导致供应链系统收益偏低；创新成本补贴机制以及垂直整合机制能够有效激励参与主体的创新积极性；成本补贴机制能够提高各主体以及整个供应链系统的收益，垂直整合机制对收益的影响主要取决于整合成本的区间范围。     

供应链的冲突机理分析及多代理系统的研究

针对目前对多代理系统在供应链中应用的研究缺乏理论体系的现状,从理论上研究了企业中存在的供应链信息不对称问题,分析了供应链中的冲突机理和principal-agent问题的特点.从供应链信息协调的角度研究了多代理系统在供应链协调中的应用,提出了一个可有效解决信息不对称问题的基于多代理系统的供应链模型,从而对有效实现企业供应链的快速重构和动态协调具有重要的指导意义.     

基于仿真的三级供应链成本优化

针对供应链这种非线性和复杂系统,为了优化供应链的总成本,提高供应链的整体竞争力,提出了一种基于仿真的优化方法。首先建立了一个三级协作供应链的系统动力学模型,供应链上的企业需要求解多个决策变量来降低供应链总成本。然后详细展示了将系统动力学模型转换为Matlab程序模型的过程,并在两个模型中使用了多组随机参数进行对比验证。最后设计了适当的遗传算法进行求解。结果表明,这种基于仿真的优化方法不仅能反映出供应链系统的动态特征,而且求解速度快、精度高,能有效解决供应链系统中的单目标或多目标规划问题。系统动力学模型结构相对固定,也不适合异构的交互环境,该方法给系统动力学模型提供了良好的补充。转换为Matlab程序模型后,可以进行深入的仿真研究,灵活设置目标函数和约束条件,详细分析系统的动态变化过程,还能为其它应用提供交互接口。     

数据赋能企业供应链智能化转型策略选择研究

针对企业供应链智能化转型投入的技术落地情景,以及供应链成员企业策略选择的外部性问题,根据供应链中供应商和制造商的不同行为策略选择的支付矩阵构建了演化博弈模型,对模型的参数进行求解和分析,并且设置数值模拟算例进行分析。结果表明,供应链主体的智能化投入策略选择与不同主体的投入成本收益转化率密切相关,演化系统的均衡随着该转化率的变化而发生变化。针对供应链企业的智能化投入中存在的“搭便车”行为,政府能够通过激励进行缓和,政府激励机制的制定也将对供应链企业智能化投入产生一定的启示。     

基于多agent合作的敏捷供应链管理系统研究

敏捷供应链正成为提高企业全球竞争力的有效手段。本文建立了基于多agent的敏捷化供应链管理系统 ,此系统是基于将企业的业务逻辑和事务处理分开的思想 ,通过供应链定义工具对企业的业务逻辑进行描述 ,利用多agent的合作 ,实现供应链的事务处理 ,从而有效地支持供应链的动态建立和过程重组 ,增强供应链系统信息分布处理和软件可重用能力     

区间灰色时滞特征的供应链建模及稳定性分析

供应链的平稳运行是供应链管理的重要基础。针对具有区间灰色时滞特征的供应链建模及其稳定性控制的难题,基于时滞系统模型,结合供应链建模中矩阵的区间灰色特性,建立了具有区间灰色时滞特征的供应链多层模型系统,并提出了一种使用李雅普诺夫(Lyapunov)函数方法,研究多层供应链结构的稳定性问题,获取了一个有效且实用的稳定性判据,给出了证明过程。为了验证该方法的有效性能,以2层区间灰色时滞供应链系统为算例,研究具有区间灰色时滞特征的供应链系统的随机稳定性问题。算例结果表明:使用Matlab 7.0计算工具,在判别矩阵U+V<0时获得一组常数值ε,在给定条件下,供应链系统随机稳定。可得出结论:该算法在保证最优解不会降低的情况下,达到了系统稳定能力增强的目的,可为实际应用提供指导。     

双因素视角下复杂产品供应链质量激励契约研究

考虑短期经济收益和长期质量声誉的综合影响,设计了一类复杂产品供应链质量激励契约,辅助主制造商诱导供应商在实现自身最优收益的同时,自发地提升外协系统的质量水平,实现质量合作主体综合效用的共赢。针对复杂产品外协系统小批量订购模式,从广义质量损失视角测度外协系统质量水平,构建供应链质量合作主体的"收益-声誉"效用函数。考虑供应商质量信息优势,构建"委托-代理"模型分析固定支付情形下复杂产品供应链质量合作的均衡解。探寻质量激励函数对合作主体综合效用的激励作用,以合作方最优质量水平离差最小为优化目标,考虑实际效用提升、有效激励和主动参与等多种约束条件,构建目标规划模型分析质量激励情形下供应链质量合作的均衡解及改进效果。针对某商用飞机公司和某航空发动机公司的质量合作开展案例研究,通过比较分析验证质量激励函数的合理性和有效性,为复杂产品供应链质量激励契约设计提供了一种新的分析思路。     

基于多agent合作的每捷供应管理系统研究

敏捷供应链正成为提高企业全球竞争力的有效手段。本文建立了基于多agent的敏捷化供应链管理系统，此系统是基于将企业的业务逻辑和事务处理分开的思想，通过供应链定义工具对企业的业务逻辑进行描述，利用多agent的合作，实现供应链的事务处理，从而有效地支持供应链的动态建立和过程重组，增强供应链系统信息分布处理和软件可重用能力。     

公平关切下制造商主导的闭环供应链定价策略

将公平关切行为引入到闭环供应链决策中,研究了制造商公平关切与零售商公平关切两种情形下的决策行为,比较分析了不同关切主体下公平偏好系数对供应链回收率、系统利润的影响。研究发现,制造商的公平偏好会提高系统的批发价与零售价,造成回收率及双方利润的降低;而零售商的公平偏好会导致批发价、零售价及供应链回收率的降低,但可以提高自身的利润;同时发现决策者不能一味地追求公平而导致供应链运作失常及社会福利的损失。     

考虑政府多政策和第三方回收的闭环供应链协调机制研究

分析政府多政策情形下第三方回收模式闭环供应链的协调问题。考虑政府多政策以及零售商主导,建立3种不同情形的供应链模型,并比较分析各情形下的供应链最优定价决策和利润。研究表明,政府多政策能够有效提高回收量并使逆向供应链中第三方利润和顾客效用增加,但正向供应链成员利润和顾客效用会减小;利润共享?费用分担契约和授权?最优回收数量契约都可以实现有效协调;协调后供应链中各主体企业的利润和顾客效用得到改善。     

A multi-agent model for the reasoning of uncertainty information in supply chains

In order to simulate the real world effectively, this paper proposes a multi-agent model that integrates a price negotiation support system based on the use of intelligent agents capable of processing information uncertainty. The certainty factor is integrated in expert systems to support the decision of agents. In the model, each agent is integrated with an expert system to deal with the uncertainty information. A real example of supply chains is chosen to show the validity of the proposed multi-agent model. Virtual companies can use the uncertainty information to support decisions. Multiple experiments are conducted to work on the coordination of the supply chain. The selling and purchasing prices in the supply chain are proposed in the experimental results. These prices are similar with the data in a real supply chain and are the optimal price strategy for the supply chain. The model was programmed using Jess and Swarm, which was run on Windows XP. The multi-agent model in the paper is beneficial to the reasoning of uncertainty information in multi-agent systems.     

多Agent系统开发框架JAFMAS及其应用

介绍了一个基于Java的多Agent应用开发系统JAFMAS.该系统为多Agent系统的开发提供了一个通用的开发平台,解决了Agent间的通信、交互和协调机制等关键问题,并以供应链系统的应用开发为例,说明了怎样利用JAFMAS类库实现多Agent系统应用程序开发的具体步骤.     

Supply Chain Management System Model of Virtual Enterprises Based on Multi-Agent

Based on the analysis of a virtual enterprise and the development of supply chain management, their integration is proposed. Then, the difference between multi-agent system modeling method and the traditional modeling method is analyzed, and a method based on Java agent framework for multi-agent systems(JAFMAS) is proposed. By using this method the virtual enterprise's supply chain management system model is established.     

基于多代理和遗传算法的协同生产调度研究

针对经典作业车间调度(Job-Shop Scheduling)问题的局限性,结合实际生产情况,提出了基于多代理机制的供应链环境下的企业间的协同生产调度(Cooperated production scheduling)系统的体系结构,结合多代理的灵活性和遗传算法的全局优化性,阐述了一种基于多代理和遗传算法的协同调度系统,并寻求适合于这种供应链环境的优化调度方案.     

ExPlanTech: Applying multi-agent systems in production planning

This paper presents work carried out within the 'ExPlanTech' project (IST-1999-20171) funded in part by the European Commission's Information Technologies Programme. The mission of the ExPlanTech technology transfer project is to introduce, customize and exploit the multi-agent production planning technology (ProPlanT multi-agent system research prototype) in two specific industrial enterprises. An agent-driven service negotiations and decision process, based on usagecentred knowledge about task requirements, substitutes the traditional production planning activity. We introduce a methodology for integration of the projectdriven production planning based on agent-based engineering within the existing enterprise resource planning system. This novel production planning technology will facilitate optimization of resource utilization and supplier chain while meeting the customer demands. This paper describes a FIPA-compliant implementation of the ExPlanTech technology at the LIAZ Pattern Shop manufacturing company. We describe the structure of the agent community, types of agents, implementation of the planning strategy and its incorporation within the real production environment.     

Resource Allocation and Power Control Policy for Device-toDevice Communication Using Multi-Agent Reinforcement Learning

Device-to-Device (D2D) communication is a promising technology that can reduce the burden on cellular networks while increasing network capacity. In this paper, we focus on the channel resource allocation and power control to improve the system resource utilization and network throughput. Firstly, we treat each D2D pair as an independent agent. Each agent makes decisions based on the local channel states information observed by itself. The multi-agent Reinforcement Learning (RL) algorithm is proposed for our multi-user system. We assume that the D2D pair do not possess any information on the availability and quality of the resource block to be selected, so the problem is modeled as a stochastic non-cooperative game. Hence, each agent becomes a player and they make decisions together to achieve global optimization. Thereby, the multi-agent Q-learning algorithm based on game theory is established. Secondly, in order to accelerate the convergence rate of multi-agent Q-learning, we consider a power allocation strategy based on Fuzzy Cmeans (FCM) algorithm. The strategy firstly groups the D2D users by FCM, and treats each group as an agent, and then performs multi-agent Q-learning algorithm to determine the power for each group of D2D users. The simulation results show that the Q-learning algorithm based on multi-agent can improve the throughput of the system. In particular, FCM can greatly speed up the convergence of the multi-agent Q-learning algorithm while improving system throughput.     

A multi-agent system for chemical supply chain simulation and management support

Modern chemical production is customer-driven and the desired delivery time for the products is often shorter than their campaign length. In addition, the raw materials supplying time is often long. These features make it desirable to provide tools to support collaborative supply chain decision making, preferably over the Internet, and where there are conflicts, compromise decisions can be quickly reached and the effects of the decisions can be quantitatively simulated. This paper des cribes such a multi-agent system (MAS) that can be used to simulate the dynamic behaviour and support the management of chemical supply chains over the Internet. Geographically distributed retailers, logistics, warehouses, plants and raw material suppliers are modelled as an open and re-configurable network of co-operative agents, each performing one or more supply chain functions. Communication between agents is made through the common agent communication language KQML (knowledge query message language). A t the simulation layer, the MAS allows distributed simulation of the chain behaviour dynamically, so that compromise decisions can be rapidly and quantitatively evaluated. Because in a chemical supply chain the scheduling of the plant often dominates the chain performance, an optimum scheduling system for batch plants is integrated into the MAS. The functions of the system are illustrated by reference to a case study for the supply and manufacture using a multi-purpose batch plant of paints and coatings.     

动态供应链谈判代理的设计及实现

面向动态供应链,引入智能代理技术,充分发挥智能多代理系统的自主性,重点就商业谈判体系以及其功能的设计与实现进行了较为深入的研究.根据业务交易的典型阶段,建立了业务谈判的多代理软件体系,给出了相应的谈判词汇表的描述.确立了谈判规则,并以DFA为工具描述谈判过程,进而实现了一个自主谈判过程.