多目标规划模型的研究

优化问题是数学建模中的一类大问题,在历年全国大学生数学建模竞赛赛题中几乎离不开优化方法。多目标规划是大规模优化问题中最常见的一种,在现实的决策过程中,决策者面临的往往是一些具有多个目标的决策问题。多目标规划恰恰就是解决这类问题的理想方法,因而有着广泛的应用前景。本文从多目标规划的意义,发展现状,研究内容,技术难点,关键技术,研究方法,市场前景及社会效益等方面进行论述,使多目标规划模型在应用上更具有普遍性。     

基于多Agent的供应链智能集成与决策研究

探讨了供应链存在的问题以及供应链集成的层次与步骤,并重点探讨了基于多Agent的供应链智能集成框架与智能化决策方法,从知识管理的角度指出了供应链智能集成的研究方向。     

基于多目标进化算法的目标规划研究

1 引言目标规划是一类十分实用的重要模型,与一般多目标最优化模型不同,这类模型并不是考虑对各个目标进行极小化或极大化,而是希望在约束条件限制下,每一个目标都尽可能地接近于事先给定的各自对应的目标值。由于这类模型在处理问题时具有比较灵活、简便的特点,因而在工程技术和管理中应用非常广泛。本文研究逼近目标规划模型:     

面向行业供应链的企业应用集成研究

供应链信息系统的集成对于提高供应链的管理水平至关重要，也是实施供应链管理系统的一个难题。介绍了EAI的内容和面临的难题，然后结合行业供应链上的企业应用的特点，给出了面向行业供应链的企业应用集成架构参考模型，进一步论述了实现集成架构模型的关键技术。最后，给出了该集成框架下一个具体的应用案例。     

面向行业供应链的企业应用集成研究

供应链信息系统的集成对于提高供应链的管理水平至关重要,也是实施供应链管理系统的一个难题。介绍了EAI的内容和面临的难题,然后结合行业供应链上的企业应用的特点,给出了面向行业供应链的企业应用集成架构参考模型,进一步论述了实现集成架构模型的关键技术。最后,给出了该集成框架下一个具体的应用案例。     

多目标规划的LINDO求解方法

按多目标优先级逐级展开,将多目标转化为线性规划,再利用LinDo求解,从而使多目标规划的求解变得简单易行。     

供应链管理三流集成

产品(实物)是从最初供应商流向最终客户,资金按照相反方向流动,而信息则双向流动。供应链管理实际上是对实物流、信息流、资金流的集成管理。     

面向供应链管理的企业应用集成技术选择模型

供应链信息系统的集成对于提高供应链管理水平至关重要,企业应用集成(EnterpriseApplicationIntegration,EAI)技术的出现对供应链信息系统的集成提供了一个新的解决方案。论文通过对供应链集成系统的分类和EAI技术的分析,提出了选择适用于不同类型系统的EAI技术的模型,通过该模型的应用,减少了企业在选择供应链信息系统集成技术时的不确定性,为有效地集成供应链信息系统提供了切实可行的方法和途径。     

两层多目标规划的罚函数法

研究了一类非线性两层多目标规划问题.在下层多目标规划问题的目标函数是严格凸函数、决策变量约束集是凸集的假设下,通过将两层多目标规划问题转化成一系列单层多目标规划问题,建立了两层多目标规划的罚函数理论,并进行了收敛性分析.从而丰富了两层多目标规划的理论,为解决实际中的两层多目标决策问题提供了有力的工具.     

基于多代理的敏捷供应链管理研究

从系统的体系结构出发，建立了基于多代理的敏捷供应链管理模型。利用软件agent负责具体的信息和事务处理，通过ECA规则调度多代理的执行。该管理模型为供应链管理系统提供了快速重构和动态扩展的方法。     

An interactive possibilistic programming approach for a multi-objective closed-loop supply chain network under uncertainty

In this article, we first propose a closed-loop supply chain network design that integrates network design decisions in both forward and reverse supply chain networks into a unified structure as well as incorporates the tactical decisions with strategic ones (e.g., facility location and supplier selection) at each period. To do so, various conflicting objectives and constraints are simultaneously taken into account in the presence of some uncertain parameters, such as cost coefficients and customer demands. Then, we propose a novel interactive possibilistic approach based on the well-known STEP method to solve the multi-objective mixed-integer linear programming model. To validate the presented model and solution method, a numerical test is accomplished through the application of the proposed possibilistic-STEM algorithm. The computational results demonstrate suitability of the presented model and solution method.     

基于物联网的集成化港口供应链协同管理探析

物联网作为新一代信息技术,在协同管理方面发挥着越来越重要的作用。同时,作为集成化程度要求较高的港口供应链,运用物联网技术进行协同管理,则是一种新的突破。拟通过分析基于物联网的集成化港口供应链协同管理的概念,设计或提出基于物联网的集成化港口供应链协同管理模式、协同管理平台及其对策。     

Values of the balanced decision making between supply chain partners

Coordination between supply chain partners is critical to effective supply chain management. In this paper, we consider two cases of decision-making structure for a simple supply chain consisting of two players: the first case in which a supply chain partner dominates the decision-making process, and the other in which two players share the decision-making process equally. According to the literature, we know a priori that the balanced decision making forges a better (financial) outcome than the dominating case does. Therefore, our primary research objective is to analyze detailed dynamics of resource allocation and sources of the benefit of the balanced decision making. Our analysis indicates that the value of the balanced decision making arises from more effective resource utilization than the dominating case does: each of the cooperative partners knows how to optimize its resource utilization better than the other does.     

基于混合整数规划的智能车横纵向一体化滚动优化决策

本文针对智能车辆的行为决策问题, 设计了基于混合整数规划的智能车横纵向一体化滚动优化决策方法. 该方法首先将纵向车速表示为非整数, 将期望车道表示为整数控制量, 建立了混合整数智能车决策简化模型; 然后, 设计了横纵向一体化滚动优化决策方法, 决策出纵向车速和换道动作, 根据系统输出与非线性约束的时域关系证明 了优化问题的递归可行性并通过遗传算法求解非线性混合整数规划优化问题. 基于车辆动力学仿真软件veDYNA 和Simulink进行了联合仿真, 并在红旗E-HS3智能车上开展了实车试验, 结果表明, 本文提出的基于混合整数规划的 智能车横纵向一体化决策方法能够实现超车、避障、跟车、停车和弯道工况下的行为决策.     

供应链库存的模糊机会约束规划模型

研究了不确定环境下的供应链库存优化问题。考虑需求为模糊量,且可能在一定条件下不满足约束条件的决策前提,用三角模糊数表示需求,结合可能性理论中的可信性测度,建立了多品种联合补充的模糊机会约束规划模型,目标函数为最小化供应链订货成本和库存成本的期望值。用遗传算法对优化模型求解,以目标函数值作为染色体适应度,给出了编码方案及选择、交叉、变异算子。用数值实例进行了仿真计算,证明了模型和算法的有效性和性能,并给出了不同置信水平下的计算结果。     

Behaviour adaptation in the multi-agent, multi-objective and multi-role supply chain

Researchers, practitioners and enterprise software providers are realising the potential of agent-based technology to automate supply chain procurement to achieve consistent, traceable decision making. As the complexity of supply chains grow, these systems will gain more attention. In this paper, we model and simulate a complex autonomous supply chain managed by computational agents that aim to minimise lead time and maximise revenue through evolutionary multi-objective optimisation. The agents are in a competitive environment where they take on the roles of both client and producer. In addition to optimising their production strategy, they also have the opportunity to dynamically fine-tune their decision parameters when it comes to selecting their own suppliers, using the Analytical Hierarchy Process. It is observed that computational agents are capable of functioning in such complex environments, effectively converging to policies in synergy with their market. Multi-objective, multi-role optimisation results in better overall supply chain performance than tests where agents have single-objectives and single-roles. Our study forms an exploratory step towards more realistic agent-based supply chains where analytical methods are unavailable.     

A tri-level programming model based on Conditional Value-at-Risk for three-stage supply chain management

For the problem of supply chain management, the existing literature mainly focuses on the research of the single-stage supply chain or the two-stage supply chain that consists of a manufacturer and a retailer. To our best knowledge, little attention has been paid to the study of a more extensive supply chain that consists of a material supplier, a manufacturer and a retailer, which is a more practical and interesting case. Therefore, based on the Conditional Value-at-Risk (CVaR) measure of risk management, this paper proposes a tri-level programming model for the three-stage supply chain management. In this model, the material supplier and the manufacturer maximize their own profit while the retailer maximize his/her CVaR of expected profit. Further, we show that the proposed tri-level programming model can be transferred into a bilevel programming model, which can be solved by the existing methods. Numerical results show that the proposed model is efficient for improving the risk management of the three-stage supply chain.     

Two-stage stochastic programming supply chain model for biodiesel production via wastewater treatment

This paper presents a two-stage stochastic programming model used to design and manage biodiesel supply chains. This is a mixed-integer linear program and an extension of the classical two-stage stochastic location-transportation model. The proposed model optimizes not only costs but also emissions in the supply chain. The model captures the impact of biomass supply and technology uncertainty on supply chain-related decisions; the tradeoffs that exist between location and transportation decisions; and the tradeoffs between costs and emissions in the supply chain. The objective function and model constraints reflect the impact of different carbon regulatory policies, such as carbon cap, carbon tax, carbon cap-and-trade, and carbon offset mechanisms on supply chain decisions. We solve this problem using algorithms that combine Lagrangian relaxation and L-shaped solution methods, and we develop a case study using data from the state of Mississippi. The results from the computational analysis point to important observations about the impacts of carbon regulatory mechanisms as well as the uncertainties on the performance of biocrude supply chains.     

供应链协同管理的绩效评估

供应链协同管理是通过对供应链系统的人力、物力、资金及信息等资源的规划、组织和控制,来实现其目标。供应链协同管理的效果如何,可通过绩效评估进行检验,他是协同管理的一个重要环节。使用平衡积分卡、粗糙集中启发式属性约简的方法和BP神经网络的理论,探索建立了平衡积分卡、启发式属性约简和BP神经网络相结合的供应链协同管理的绩效评估模型。并结合一个实例,首先对其基于平衡记分卡的指标体系进行了约简,然后将约简的评价指标输入到BP神经网络中进行智能训练,最后把评估的样本输入到训练好的BP网络中得出供应链协同管理的绩效评估值,评估结果与实际结果基本吻合。     

分布式数据库在商业供应链系统中的应用

随着网络中数据库应用的发展,使得分布式数据库的应用领域得到快速的扩展。针对商业流通企业大规模、分散式经营以及集团化管理的模式,提出了在商业供应链系统中采用分布式数据库的结构设计方案,对供应链系统的数据库体系进行了分析,对在数据库设计过程中的一些关键问题进行探讨并给出了解决方法。以Oracle 9i数据库系统为例,介绍了采用增量复制、分组、半连接技术,进行数据复制、解决数据冲突以及进行查询优化的实现方法。