Game Theory Based Decision Coordination Strategy of Agricultural Logistics Service Information System

Under the background of“Internet plus”rapid development,the agricultural logistics industry should apply information technology to every link of the agricultural product logistics industry chain.By making full use of the decision making module of the agricultural logistics information system,we can realize the full sharing of information and data resources,which makes the decision-making scheme of the agricultural logistics information system more optimized.In real economic society,the uncertainty and mismatch between the customer’s logistics service demand and the logistics service capability that the logistics service function provider can provide,that is,when the two information are asymmetric,how to use the third-party contract to coordinate the income and profit distribution of the two,to make the information system decision making more reasonable?This paper mainly studies the coordination scheme of agricultural logistics information system decision making under uncertain output and demand information by introducing the spot market.A joint coordination strategy based on revenue sharing and penalty feedback contracts proposes decentralized decision making based on game theory.Experiments show that the flexible ordering strategy proposed in this paper can reduce the logistics service supply chain’s uncertainty and significantly improve the logistics service supply chain’s overall income level through coordination contracts.

Early Building Design:Informed decision-making by exploring multidimensional design space using sensitivity analysis

This paper describes a novel approach to explore a multidimensional design space and guide multi-actor decision making in the design of sustainable buildings.The aim is to provide proactive and holistic guidance of the design team.We propose to perform exhaustive Monte Carlo simulations in an iterative design approach that consists of tw o steps:1) preparation by the modeler,and 2) a multi-collaborator meeting.In the preparation phase,the simulation modeler performs Morris sensitivity analysis to fixate insignificant model inputs and to identify non-linearity and interaction effects.Next,a representation of the global design space is obtained from thousands of simulations using low-discrepancysequences(LPτ) for sampling.From these simulations,the modeler constructs fast metamodels and performs quantitative sensitivity analysis.During the meeting,the design team explores the global design space by filtering the thousands of simulations.Variable filter criteria are easily applied using an interactive parallel coordinate plot w hich provide immediate feedback on requirements and design choices.Sensitivity measures and metamodels show the combined effects of changing a single input and how to remedy unw anted output changes.The proposed methodology has been developed and tested through real building cases using a normative model to assess energy demand,thermal comfort,and daylight.

Decision-making approach by employing grey incidence analysis and group negotiation

For the problems of the consistency ranking of the group decision-making scheme,from the view of group negotiation and system coordination,the grey incidence analysis and Nash bargaining model are used to establish a consistency group decision-making method.First,the concepts of the consensus partial decision-making program and the consensus overall ideal decision-making program are defined,and then a multi-object optimization model is constructed based on the satisfaction maximization of group negotiation and deviation minimization of system coordination to determine the consensus partial decision-making program and the consensus overall ideal decision-making program.Moreover,the grey incidence analysis is exploited to measure the close degrees between them.Finally,a real case of the online product evaluation verifies the validity and rationality of the proposed model.

Supply chain decisions and coordination in the presence of an imperfect spot market

This study considers a supply chain consisting of a commodity supplier and a final product manufacturer with uncertain demand.In addition to purchasing from the supplier through a forward contract,the manufacturer can adjust their inventory by trading the commodity in an online spot market after observing the actual demand.However,the spot market is imperfect in that transactions cannot be certainly realized and come with additional transaction costs.Furthermore,the spot price is volatile such that overly relying on the spot market is unwise.To investigate how the spot market affects the decisions and coordination in a supply chain,we develop a game-theoretical model incorporating spot trading.We derive the optimal ordering decision in a centralized supply chain,as well as the supplier's and manufacturer's equilibrium pricing and ordering decisions in a decentralized supply chain.The impact of the imperfect spot market on the optimal decisions and profits is analyzed.This study also demonstrates how the supply chain can be coordinated in the presence of an imperfect spot market.Finally,a numerical analysis is performed to examine the analytical results.Our results indicate that the spot market can generally improve the performance of the centralized supply chain and benefit the manufacturer in the decentralized one.However,it can be detrimental to the supplier.The supply chain can be coordinated by a revenue-sharing contract,and both parties'profits can be improved.Our findings suggest that the manufacturer could take advantage of the spot market,and the supplier should attempt to integrate or coordinate the supply chain to share the benefits of spot trading.

Control Method of Effect of Robust Optimization in Multi-Player Multi-Objective Decision-Making

In the real situations of supply chain, there are different parts such as facilities, logistics warehouses and retail stores and they handle common kinds of products. In this research, these situations are focused on as the background of this research. They deal with the common quantities of their products, but due to their different environments, the optimal production quantity of one part can be unacceptable to another part and it may suffer a heavy loss. To avoid that kind of unacceptable situations, the common production quantities should be acceptable to all parts in one supply chain. Therefore, the motivation of this research is the necessity of the method to find the production quantities that make all decision makers acceptable is needed. However, it is difficult to find the production quantities that make all decision makers acceptable. Moreover, their acceptable ranges do not always have common ranges. In the decision making of car design, there are similar situations to this type of decision making. The performance of a car consists of purposes such as fuel efficiency, size and so on. Improving one purpose makes another worse and the relationship between these purposes is tradeoff. In these cases, Suriawase process is applied. This process consists of negotiations and reviews of the requirements of the purposes. In the step of negotiations, the requirements of the purposes are share among all decision makers and the solution that makes them as satisfied as possible. In the step of reviews of the requirements, they are reviewed based on the result of the negotiation if the result is unacceptable to some of decision makers. Therefore, through the iterations of the two steps, the solution that makes all decision makers satisfied is obtained. However, in the previous research, the effects that one decision maker reviews requirements in Suriawase process are quantified, but the mathematical model to modify the ranges of production quantities of all decision makers simultaneously is not shown. Therefore, in this research, based on Suriawase process, the mathematical model of multi-player multi-objective decision making is proposed. The mathematical model of multi-player multi-objective decision making by using linear physical programming (LPP) and robust optimization (RO) in the previous research is the basis of the methods of this research. LPP is one of the multi-objective optimization methods and RO is used to make the balance of the preference levels among decision makers. In LPP, the preference ranges of all objective functions are needed, so as the hypothesis of this research. In the research referred in this research, the method to control the effect of RO is not shown. If the effect of RO is too big, the average of the preference level becomes worse. The purpose of this research is to reproduce the mathematical model of multi-player multi-objective decision making based on Suriawase process and propose the method to control the effect of RO. In the proposed model, a set of the solutions of the negotiation problem is obtained and it is proved by the result of the numerical experiment. Therefore, the conclusion that the proposed model is available to obtain a set of the solutions of the negotiation problems in supply chain.

A NEW APPROACH TO THE DESIGN OF A SYSTEM FOR FEATURE EXTRACTION BASED ON HUMAN-COMPUTER COLLABORATIVE TACTIC

We are involved in an embarrassing situation that the limited capability of automated feature extraction in digital photogrammetric systems cannot satisfy the increasing needs for rapid acquisition of semantic information for applications. Facing this challenge, a new tactic, Human-Computer Collaborative (HCC) tactic, and a corresponding new method, Operator-Object Directed (OOD) method, are proposed for the design of a system for feature extraction from large scale aerial images. We hold that in almost all technical complex systems, full automation will be neither technically feasible nor socially acceptable. The system should be designed to optimize through the cooperative operation with two agents in the system: the hurtan and the computer.

算法透明的困境及规制路径研究

算法决策技术的兴起推动了社会发展,同时也带来了算法黑箱、算法合谋、算法操纵等技术和社会风险,必须对算法进行规制以控制风险。算法透明是进行算法规制的前提和基础,由于技术和制度上的障碍,完全彻底的算法透明不现实也不合理,在具体场景中追求有限、适当的算法透明才是有意义的。在算法透明的落实和保障上,行政规制具有独特的优势,通过构建刚柔并济的行政规制体系、促进企业算法合规监管、推进算法备案制度、追究算法披露不当行为责任四项具体行政规制措施,监督和保障算法透明制度的运行,实现科技创新与社会安全之间的平衡与协调。

加权区间值犹豫模糊集的群决策方法

为了在区间值犹豫模糊集(IVHFS)中体现出决策专家的重要性,把所有评审专家的综合权重注入IVHFS中,进而定义了加权区间值犹豫模糊集(WIVHFS).将WIVHFS用三维点坐标(由区间值隶属度的中位数、区间值隶属度的清晰度以及评审专家综合权重构成)进行刻画,在此基础上给出了加权区间值犹豫模糊元(WIVHFE)的相关运算;基于WIVHFE的相关运算采用熵值法计算测评准则客观权重,利用0-1优先关系矩阵来获取任意2个备选方案的总测评准则权重优势值与总测评准则权重劣势值,并依据二者之间的大小排序方案.最后,通过一个具体案例说明了文中理论与方法的可行性.

碳交易下考虑公平关切的低碳供应链定价及协调机制研究

为落实政府碳减排要求并保证企业经济的可持续发展,碳交易机制成了一种有效的经济手段。碳交易背景下,制造企业为实现低碳目标而增加减排投资成本,往往更容易关注利润分配的公平性。此时,如何基于公平关切偏好进行减排投资和利润分配成为供应链协调决策的重点。以一家生产低碳产品的制造商和一家负责产品销售的零售商为对象,综合考虑碳交易机制、企业碳减排投资和公平关切偏好因素的影响,构建了一个可持续的低碳供应链,并利用博弈理论和收益分配绝对公平方法,探讨了制造商公平关切决策情形下供应链系统最优定价以及减排决策过程,进一步采用碳减排成本分担契约对供应链系统决策过程进行协调,并获得了最优的契约参数值。研究结果表明:制造商采取了提高产品批发价格和降低减排率的策略以减少因减排技术投资而产生的利润分配不公平对待,该策略损失了自身和合作者的利润。为了实现低碳供应链成员之间利益的有效协调,本文设计的成本分担契约在提高供应链系统减排率的同时还可以实现各成员利润的帕累托改进。另外,碳交易机制有利于促使企业进行碳减排投资以提高产品的减排水平。研究结果为进一步改善上下游企业之间的关系和促进供应链系统经济与环境的可持续发展提供参考。

MULTI-FIGHTER COORDINATED MULTI-TARGET ATTACK SYSTEM

A definition of self-determined priority is used in airfight decision firstly. A scheme of grouping the whole fighters is introduced, and the principle of target assignment and fire control is designed. Based on the neutral network, the decision algorithm is derived and the whole coordinated decision system is simulated. Secondly an algorithm for missile-attacking area is described and its calculational result is obtained under initial conditions. Then the attacking of missile is realized by the proportion guidance. Finally, a multi-target attack system. The system includes airfight decision, estimation of missile attack area and calculation of missile attack procedure. A digital simulation demonstrates that the airfight decision algorithm is correct. The methods have important reference values for the study of fire control system of the fourth generation fighter.

老旧小区绿色改造不同产权业主决策协同机制研究

老旧小区绿色改造是实施节能减排、“双碳目标”战略、建筑可持续高质量发展和生态宜居城市建设的建筑实践。从城市更新系统要求考虑,老旧小区绿色改造应打破现有小区界限实施一体化系统改造,老旧小区绿色改造实施过程是基于同产权业主共同决策驱动的行为活动结果,协调不同产权业主利益关系是保障老旧小区绿色改造稳步推进的内在要求。基于老旧小区产权多样性界定与特性分析,依据演化博弈理论,从探寻老旧小区绿色改造业主决策协同机制出发,构建共有产权业主与私有产权业主决策行为演化博弈模型,并运用复制动态方法分析不同产权业主群体策略演化过程,得到改造成本、经济收益、环境收益、施工影响是双方决策协同的关键影响因素。进而从创新融资模式、建立共有产权住宅产权人费用分摊机制、推进项目全过程管理制度等三个方面提出决策协调策略。期望以业主决策协同驱动主体行为合力推动老旧小区绿色改造发展进程。

基于协调度的海上专业救助力量部署决策研究

针对当前海洋生产结构调整带来的海上救助需求变化和缺少救助力量部署决策工具等问题,提出一种基于协调度的海上救助力量部署复合决策方法。通过建立协调度评价模型对救助单元救助能力和海上救助需求进行协调性分析,运用层次分析法(AHP)对海洋经济发展中存在的海上救助需求进行评价,使用基本图形分析法建立各海洋产业对不同等级的专业海洋救助船的需求模型,构造空间分布。运用此方法对专业救助力量实际值守海域进行计算及分析,进一步优化部署方案。结果表明:通过此方法得到的部署决策意见与多数可查的海上救助应急处置情况十分接近,验证了该方法的有效性。

老旧工业厂区绿色改造项目节能服务公司与业主决策协调机制研究架构

老旧厂区绿色改造项目是一项涉及多方利益主体的系统工程,决策与利益冲突下的协调路径是主体协同合作的关键。立足项目治理视角,分析绿色改造内容与对象的综合性、收益主体广泛特性带来的节能服务公司与业主决策协调的复杂困难性;提出节能服务公司与业主决策协调系统架构思路,阐述决策协调影响机理、行为策略选择、实施机理、运行机制与效果度量的内在关联关系,以此架构老旧工业厂区绿色改造项目节能服务公司与业主决策协调机制研究内容,以期丰富项目决策理论,有效推动老旧厂区绿色改造事业发展。

基于安全深度强化学习的电网有功频率协同优化控制

可再生能源占比不断增加给互联电网频率控制带来严峻考验.由于常规的自动发电控制(AGC)策略没有考虑电网潮流安全约束,所以传统方法根据专家知识和经验进行尝试性发电机功率调整,需耗费较多时间;基于最优电力潮流的互联电网AGC优化模型由于非凸性和大规模性,求解时间较长且存在收敛性问题.鉴于常规深度强化学习具有“离线训练、在线端对端形成策略”的优点,但在动作探索过程中无法保证系统安全性,提出一种基于安全深度强化学习的电网有功频率协同优化控制方法.首先,将电网频率控制建模为约束马尔可夫决策过程,对决策过程添加相关安全约束进行智能体设计;然后,基于华东电网实际系统算例对智能体进行训练和性能提升;最后,对比智能体决策与常规AGC策略效果.结果表明:所提方法在多种运行方式下可快速生成有功频率控制策略,且保证系统频率恢复过程中电网的安全性,可辅助调度员在线决策.

基于改进多智能体Nash Q Learning的交通信号协调控制

为了优化区域交通信号配时方案,提升区域通行效率,文章提出一种基于改进多智能体Nash Q Learning的区域交通信号协调控制方法。首先,采用离散化编码方法,通过划分单元格将连续状态信息转化为离散形式。其次,在算法中融入长短时记忆网络(Long Short Term Memory,LSTM)模块,用于从状态数据中挖掘更多的隐藏信息,丰富Q值表中的状态数据。最后,基于微观交通仿真软件SUMO(Simulation of Urban Mobility)的仿真测试结果表明,相较于原始Nash Q Learning交通信号控制方法,所提方法在低、中、高流量下车辆的平均等待时间分别减少了11.5%、16.2%和10.0%,平均排队长度分别减少了9.1%、8.2%和7.6%,平均停车次数分别减少了18.3%、16.1%和10.0%。结果证明了该算法具有更好的控制效果。

人工智能如何驱动政府循证决策创新?——一个从知识视角出发的探讨

循证决策是政府提高公共决策质量、应对时代变革的重要途径。本文从循证决策的底层逻辑——知识视角出发,梳理并探讨了循证决策由传统上基于经验知识进行决策到人工智能驱动下的决策知识生成特点以及循证决策创新机制。研究发现:循证决策的核心基础是各方行动者所拥有的知识,主要包括基于逻辑分析的“理性知识”和基于经验的“直觉知识”,同时科学研究知识亦作为循证决策的重要参考。人工智能驱动下的循证决策体现出人机不断“迭代”互动的协同决策特征,这一过程的机制创新主要体现在政府决策理念的回应性与前瞻性提升、决策权力的标准化与规范化运行、决策范式的实时性与灵活性改善以及决策过程的民主性与公共价值性彰显。同时,应注重循证决策中人工智能应用存在的诸多制约因素,如技术的成熟度与可靠性、决策者的认知与接受程度、政府组织的制度与政策环境、数据的隐私安全与利用的责任问题等。

协调分析法在机电产品质量评价中的应用

为全面综合评价机电产品质量,提高评价结果准确性,在分析机电产品质量影响因素基础上,构建产品质量评价指标体系。应用模糊-熵权法确定指标权重,基于妥协原理,采用协调分析法建立综合考虑各评价指标优缺点的机电产品质量评价模型;并结合产品质量评价决策流程,输出评价结果,进而为企业制定产品采购方案提供参考;最后以某数控系统生产厂家采购编码器产品为例进行应用说明。结果表明:综合考虑产品质量优缺点的评价模型简单、操作方便,评价结果客观可信。

“统筹-决策-迭代”——福州市中心城区老旧工业园区提质升级探索

我国各大城市老旧工业园区转型诉求日益增多。针对复杂的园区企业运营与空间建设现状,本文基于福州市中心城区以金山工业园橘园洲片区为代表的老旧工业园区提质升级实践,提出“统筹-决策-迭代”模型。该模型旨在探索针对老旧工业园区提质升级过程中所面临的扩容空间受限、利益协调难度大、政策资源匹配度差等挑战,通过园城共谋的转型方向引导、精准的升级模式定制、政策匹配与空间方案设计及实时化的园区运营管理,推动老旧工业园区的提质升级与低效工业用地的有效盘活,保障园区健康可持续发展与城市创新产业升级。

服务与价格竞争的物流外包协调决策模型研究

当前,各制造企业之间的竞争呈现出价格与服务协同竞争的局面。构建由两个制造企业与一个物流服务商所组成的物流外包竞争决策模型,结果显示:企业物流外包的整体利润在集中决策时优于分散决策;集中与分散决策时产品的销售价格与服务水平受到价格交叉指数与服务代替指数的影响;参与利润共享与成本分摊协调契约之后,制造企业为“绝对获益方”,同时,当各指数的取值在有效范围内时,物流服务商的利润也将增加,但当超出有效范围时,制造企业需为物流服务商提供一定的弥补措施。

考虑销售努力的双渠道供应链定价决策与协调

随着电子商务的发展,许多零售商逐渐开拓线上渠道,并通过双渠道进行产品的销售。然而,如何进行科学决策,实现自身利润的最大化成为供应链成员普遍面临的难题。基于此,以单一零售商和单一供应商组成的生鲜农产品双渠道供应链为研究对象,考虑零售商销售努力,分析双渠道供应链的定价决策,并设计协调契约实现供应链协调。研究发现:在两种决策下,消费者对新鲜度、销售努力水平敏感度的提高均会增加供应链系统的整体利润;与分散决策相比,集中决策下双方合作更为紧密,供应商愿意提供更高的保鲜努力水平,零售商愿意提高销售努力水平,此时供应链整体利润更高;“两部定价法+批发价格”协调契约可以促进双方开展合作,降低线上和线下渠道价格,提高保鲜努力水平和销售努力水平,实现帕累托改进,使供应链整体利润达到集中决策时的水平。