基于MAS和GA的滚动窗口动态调度方法

根据动态环境下移动机器人滚动窗口路径规划法的基本思想,将多代理系统(Multi Agent System,MAS)、遗传算法(Genetic Algorithm,GA)与滚动窗口法有机地结合起来,提出了一种新的生产车间动态调度方法。该方法用多代理系统建立车间调度框架,将车间调度过程分成若干个工序窗口,每个窗口中含有一个以上的工序。每个窗口打开时,执行代理首先自动重新获取所有机床状态信息和需要调度的工件信息,再启动遗传算法求得该窗口内调度的最优解,窗口在事件调度和周期调度的综合控制下向前滚动。这种新方法可以根据环境变化,自由选择窗口大小,具有很强的实用性。仿真结果表明:对于给定的生产环境,可以找到一个最佳窗口大小,使得车间调度结果最优。     

易腐食品二级供应链生产调度与配送路线的协同优化

研究了一类生命周期服从负指数分布的易腐食品,综合考虑配送的软时窗约束以及需求和运输时间的随机性,以供应链整体利润最大化为目标,建立了生产商-零售商二级供应链模式下易腐食品生产调度与配送路线协同优化的数学模型。设计了改进的遗传算法和随机模拟技术相结合的混合智能算法求解模型。最后以某餐饮服务公司的生产调度和配送路线的协同优化问题为例,并基于Solomon算例数据设计了不同规模的测试算例对模型和算法的有效性进行了验证。     

多车间协同调度平台的研究与应用

针对传统企业在分布式制造模式下实现多个车间之间生产计划与调度的协作问题,从企业全局出发,研究多车间生产计划调度方法,提出采用多代理和规则引擎技术在制造执行系统(MES)中构建调度协同平台的解决方案.在扩充MES系统协同调度功能的基础上,实现不同车间生产制造信息共享,提高了制造企业各车间协同生产的效率.     

基于代理和遗传算法的供应链优化模拟

在本文的研究中，试图用具有智能的多代理人系统模拟供应链的运行，并且运用遗传算法来优化供应链中代理(agent)的决策行为，从而提高供应链的运行效率，降低供应链运行的总成本。     

基于Agent的供应链运作仿真技术的研究

在给多个智能代理分别赋予生产运作的各种知识，如库存管理、生产计划等之后．通过多个智能代理协同合作，对供应链中企业的生产运作过程进行仿真。在研究该仿真系统的智能代理的内部任务、结构、多代理通讯机制等实现技术基础上，实现了该系统，并给出了一个供应链仿真的结果。     

多品种小批量订单型企业生产调度优化

目的研究多品种小批量订单型企业的生产调度优化问题,方法针对S公司的生产现状,应用遗传算法思想设计调度优化方案,采用不等长矩阵的编码方式实现订单的批量生产及车间排产的方案。结果通过仿真分析和S公司生产调度的实际应用,验证了该算法的可行性及有效性。结论基于遗传算法的调度优化算法实现了多品种小批量流程型生产企业生产调度优化,达到了缩短生产周期、有效利用生产资源的目的。     

基于DBR系统的敏捷供应链协同机制

基于单一生产系统内部DBR生产计划与控制系统的实现机制,通过对其应用范围的进一步扩展,提出了供应链管理环境下DBR系统运作的六条基本原理,构建了供应链环境下DBR系统的基本框架,从计划、缓冲与控制机制三个方面对其实现机制进行了探讨.提出了支持DBR系统运作的供应链协同计划与控制模型,该模型基于单一节点企业内部DBR系统和供应链DBR系统的共同运作,通过面向订单对象的分布式生产控制模式和电子看板,实现供应链系统的协同计划与控制.     

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。     

考虑风电消纳的源-荷协同优化调度策略

为提升风电消纳比例,提出一种基于遗传算法的源-荷协同调度策略。旨在通过负荷侧需求响应与源侧发电机组共同参与电网优化调度,缓解由于风电反调峰特性导致的大规模弃风问题。在电力用户自愿参与电网调度的基础上,分析激励型需求响应参与电网调度对风电消纳的影响机理,以系统总成本最低为目标建立源-荷协同优化调度模型,在保证系统安全、可靠的前提下,采用遗传算法对模型进行求解。利用Matlab对算例进行仿真计算,与仅考虑源侧优化的调度策略相比,风电消纳比例提高了27.56%,总调度成本降低了4 798元,验证了所提策略对于提升风电消纳的有效性。     

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.     

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.     

Proposal of a multi-agent model for the sustainable truck scheduling and containers grouping problem in a Road-Rail physical internet hub

Physical Internet (PI) was introduced as a global standardised and interconnected logistics system based on PI-nodes, PI-movers and PI-containers as a mean toward global logistics sustainability. One important issue regarding PI-nodes concerns the planning and scheduling of operations and the management of PI-containers, both in a deterministic and a perturbed environment. This research considers the Road-Rail PI-hub sustainable truck scheduling and PI-containers grouping problem. In our research we consider the weighted sum of the number of used wagons, the internal distance travelled by PI-containers from PI-docks to wagons as well as the trucks’ tardiness, which translate the search for sustainable logistics. In this paper, an effective and reactive multi-agent system based model (MAS) is developed for the resolution of the trucks scheduling and PI-containers grouping. To ensure the efficiency of the MAS and improve the quality of each of its solutions, three concurrent hybrid meta-heuristics are embedded within three parallel scheduling agents. Then, a mixed integer linear programming model (MILP) is proposed to evaluate the performance of the MAS. Finally, the MAS is also evaluated under internal perturbations. The obtained results show the ability of the MAS to provide alternative sustainable solutions by rescheduling trucks in case of disruptions.     

Multi-agent systems applications in manufacturing systems and supply chain management: a review paper

This paper offers a review of the development and use of multi-agent modelling techniques and simulations in the context of manufacturing systems and supply chain management (SCM). The objective of the paper is twofold. First, it presents a comprehensive literature review of current multi-agent systems (MAS) research applications in the field of manufacturing systems and SCM. Second, it aims to identify and evaluate some key issues involved in using MAS methods to model and simulate manufacturing systems. A variety of different MAS applications are reviewed in three different classified research areas: production design and development, production planning and control, and SCM. In presenting a detailed taxonomy of MAS applications, the paper describes MAS application domains from five different perspectives. The review suggests the MAS approach represents a feasible framework for designing and analysing real-time manufacturing operations, since the approach is capable of modelling different levels of agent behaviour and dynamical interactions. The paper also highlights a number of key issues which have to be taken into account in attempting to design MAS-based research paradigms for future applications in manufacturing systems.     

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     

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.     

Flexible job-shop scheduling/rescheduling in dynamic environment: a hybrid MAS/ACO approach

In real-world manufacturing, disruptions are often encountered during the execution of a predetermined schedule, leading to the degradation of its optimality and feasibility. This study presents a hybrid approach for flexible job-shop scheduling/rescheduling problems under dynamic environment. The approach, coined as ‘HMA’ is a combination of multi-agent system (MAS) negotiation and ant colony optimisation (ACO). A fully distributed MAS structure has been constructed to support the solution-finding process by negotiation among the agents. The features of ACO are introduced into the negotiation mechanism in order to improve the performance of the schedule. Experimental studies have been carried out to evaluate the performance of the approach for scheduling and rescheduling under different types of disruptions. Different rescheduling policies are compared and discussed. The results have shown that the proposed approach is a competitive method for flexible job-shop scheduling/rescheduling for both schedule optimality and computation efficiency.     

基于多代理系统的微电网多目标优化调度

微电网在并网情况下的多目标稳定运行是微电网运营和建设的基本要求。从并网型微电网的经济目标和环保目标出发,建立微电网多目标优化模型,其中经济目标考虑分布式电源的燃料费用、运行维护费用、启停费用和与大电网的能量交互费用,环保目标考虑污染气体的排放量。提出一种基于多代理系统（multi-agent system,MAS）的分时电价机制下储能装置的调度策略,并且采用改进的NSGA-Ⅱ算法优化可控微源和储能装置的出力。以某地区微电网单元为例进行仿真,验证了所建模型和改进算法的有效性。试验结果表明,改进的NSGA-Ⅱ算法性能更优,所提出的策略可以控制储能装置一个周期内的充放电次数,延长使用寿命。     

Managing warehousing in an agile supply chain environment: an F-AIS algorithm based approach

In recent years, application of the agile concept in the manufacturing sector has been researched extensively to reduce the varying effect of customer demands. However, most of the research work is focused on the shop floor of different manufacturing processes, while issues concerning the control of warehouse scheduling in a supply chain have been neglected so far. Realising this in the present research an attempt has been made to address the scheduling aspect of a warehouse in an agile supply chain environment. To resolve the warehouse problem in this paper, the authors have proposed a new Fuzzy incorporated Artificial Immune System Algorithm (F-AIS). This algorithm encapsulates the salient features of a fuzzy logic controller and immune system. The proposed algorithm has been compared with genetic algorithm (GA), simulated annealing (SA) and artificial immune system (AIS) algorithm to reveal the efficacy of the proposed F-AIS algorithm.