Analyzing information-enabled stockout management under vendor-managed inventory

We develop a mechanism under vendor-managed inventory (VMI) by which a manufacturer provides an incentive contract to a retailer to convert lost sales stockouts into backorders. An incentive contract is required since the retailer’s efforts are not directly observable. We first show that when there are no limits on order quantities or inventory levels imposed on the manufacturer, the manufacturer will push inventory onto the retailer. The manufacturer minimizes the possibility for lost sales stockouts by maintaining high inventory levels at the retailer rather than by paying incentives to the retailer. However, modern information systems (IS), such as radio frequency identification (RFID), allow the retailer to monitor inventory at its premises and to enforce limits on order quantities. With strict limits on order quantities, the manufacturer will provide incentives to the retailer to convert lost sales stockouts to backorders. We analyze the conditions under which these incentive payments are likely to be highest.     

A control-theoretic view on incentives

The idea of declaring a reward (punishment) for a decision maker according to his particular choice of action in order to induce certain ‘desired’ behavior on the part of the decision maker is known as incentive (threat). This practice is age old. However, only in recent years have the notions been formalized. In the development of a control-theoretic view on incentives, we first investigate the deterministic version of the incentive problem. This reveals the basic simple idea behind the problem. It also illustrates the different possibilities introduced by the presence of dynamics and multi-follower nature of the problem. This is followed by two variants of the stochastic version of the problem where we concentrate on the role of uncertainties. Relationship to economic literature is also discussed.     

Analysis of asynchronous polynomial root finding methods on adistributed memory multicomputer

We have studied various implementations of iterative polynomial root finding methods on a distributed memory multicomputer. These methods are based on the construction of a sequence of approximations that converge to the set of zeros. The synchronous version consists in sharing the computation of the next iterate among the processors and updating their data through a total exchange of their results. In order to decrease the communication cost, we introduce asynchronous versions. The computation of the next iterate is still shared among the processor, but the updating is done by using only nearest neighbor communications. We prove that under weak conditions, these asynchronous versions are still locally convergent, even if their convergence orders are reduced. We analyze the behavior of the asynchronous methods in function of their delay, the topology of the interconnection network, and the elementary computation and communication times. We have implemented and compared these methods on a hypercube multicomputer     

时滞系统方法的网络控制系统的研究

针对普遍存在的采样器和零阶保持器异步这一现象,研究了该类网络控制系统的状态反馈控制问题。首先,以事件驱动的零阶保持器的更新时刻为时间标识,并考虑到网络的诱导时延和数据丢包,建立网络控制系统的采样闭环模型,并转化为状态中连缀着两个时滞变量的时滞系统。然后,利用相应的时滞系统方法,对闭环网络控制系统进行了稳定性分析和控制器综合。最后,通过仿真实例验证了所得结果的正确性。     

抖动偏频激光陀螺整周期采样对捷联惯导姿态解算的影响

抖动偏频激光捷联惯导系统中,三个激光陀螺之间机械抖动频率一般互不相同.当陀螺输出采用整周期锁存方式时,导航计算机定时采样系统采集到的三个陀螺信号,隐含着陀螺输出的不同步,在捷联惯导解算中将产生姿态解算的不可交换误差,在圆锥运动环境下误差更加严重.介绍了整周期采样时陀螺输出的不同步现象,在圆锥运动条件下对不同步问题进行仿真,仿真结果表明不同步是引起姿态解算误差的主要因素,不同步误差远远超过同步采样条件下的姿态解算误差,因此在捷联惯导系统角运动剧烈时应当予以重视.     

委托股权证明共识机制的改进研究

针对委托股权证明（Delegated Proof of Stake,DPoS）共识机制系统中节点活跃度不高、错误节点剔除不及时、记账收益分配不合理等问题,提出了一种改进方案。改进方案主要改进了DPoS的计票机制和激励机制。改进的计票机制将节点的更多信息纳入了计票范围,使得选票能够更全面地反映节点的信用情况。根据节点的投票记录,动态调整节点选票的权重加快错误节点的剔除。对于激励机制的改进分为投票激励和记账激励两个部分,投票激励针对所有参与共识的节点给予相应的激励,激励系统中的节点积极参与投票。记账激励是根据博弈论中的权利指数来对收益进行二次分配,使得分配机制更为合理,有利于降低了系统的中心化趋势。通过实验验证了改进方案的有效性。     

Incentives versus value in manufacturing systems: An application to high-speed milling

Optimal parameter selection is an important aspect of optimizing system performance. This paper examines the effect of different incentive structures, including reward and penalty based structures, for employees within an engineering firm on the value captured by that firm. Incentives are used to communicate the firm's values to the employee without revealing the firm's value function. We use a high-speed milling example to illustrate the approach and derive results. We show that, in certain cases, simple incentive structures can be aligned such that they induce profit maximizing behaviour. In other cases, we show that incentive structures result in a loss of value that we term the value gap. In the milling case considered, reward-based incentives coincide with optimal parameters while penalty-based incentives result in a greater than four-fold increase in costs. The effect of uncertainty within a system can also be analysed. We consider uncertainty in the process dynamics as well as tool life and that the inclusion of uncertainty in the analysis may not change the results in some cases.     

基于声誉的移动众包系统的在线激励机制

在大数据环境下,对移动众包系统的研究已经成为移动社会网络（MSN）的研究热点。然而由于网络个体的自私性,容易导致移动众包系统的不可信问题,为了激励个体对可信策略的选取,提出一种基于声誉的移动众包系统的激励机制——RMI。首先,结合演化博弈理论和生物学中的Wright-Fisher模型研究移动众包系统的可信演化趋势;在此基础上,分别针对free-riding问题和false-reporting问题建立相应的声誉更新方法,从而形成一套完整的激励机制,激励感知用户和任务请求者对可信策略的选取;最后通过模拟实验对提出的激励机制的有效性和适应性进行了验证。结果显示,与传统的基于社会规范的声誉更新方法相比,RMI有效地提高了移动众包系统的可信性。     

区块链赋能的高效物联网数据激励共享方案

近年来,随着大量设备不断地加入物联网中,数据共享作为物联网市场的主要驱动因素成为了研究热点.然而,当前的物联网数据共享存在着出于安全顾虑和缺乏激励机制等原因导致用户不愿意参与共享数据的问题.在此背景下,区块链技术为解决用户的信任问题和提供安全的数据存储被引入到物联网数据共享中.然而,在构建基于区块链的安全分布式数据共享...     

Optimizing channel profits with threshold incentives and alternative pricing schemes

We analyze manufacturers' trade promotions that are offered in the form of threshold incentives. In such programs, the incentive is given if the retailer's order/sales quantity exceeds a pre‐specified threshold level, and can be offered as a lump‐sum payment or on a per‐unit basis. The manufacturer determines the incentive terms and her wholesale price; in return, the retailer reacts with his profit‐maximizing decisions, which ultimately impact the market demand and total channel profits. Modeling two alternative pricing schemes by the retailer, we investigate the performance of threshold incentives from the channel perspective. We find that the threshold incentives optimize channel profits in equilibrium when the retailer exercises first‐degree price discrimination, but they lead to suboptimal channel efficiency when the retailer implements uniform pricing. We extend our models to address demand uncertainty and an alternative form of incentive scheme, and we generate further insights from numerical examples.     

考虑信誉更新的移动群智感知在线激励机制研究

激励更多用户参与感知任务并提供高质量数据是移动群智感知研究的热点问题之一。针对在线到达的激励机制场景中,参与用户提供数据的质量以及其信誉值没有得到足够重视等问题,本文提出用户在线参与感知任务的信誉评价方法并构建其信誉评价模型。综合考虑用户历史和现实的信誉记录,建立信誉更新算法模型,设计基于信誉更新的多阶段在线激励机制(Reputation-updated online mechanism,ROM)。仿真结果表明,该算法能够帮助平台获得更好的效用,提高收集数据的质量从而提高雇佣效率。     

不确定工业过程运行指标异步更新强化学习决策算法

运行指标决策问题是实现工业过程运行安全和生产指标优化的关键. 考虑到多运行指标决策问题求解的复杂性和工业过程生产条件动态波动引发生产指标状态的不确定性, 提出了一种策略异步更新强化学习算法自学习决策运行指标, 并给出算法收敛性的理论证明. 该算法在随机自适应动态规划框架下, 利用样本均值代替计算生产指标状态转移概率矩阵, 因此无需要求生产指标状态转移概率矩阵已知. 并且通过引入时钟和定义其阈值, 采用集中式策略评估、多策略异步更新方式用以简化求解多运行指标决策问题, 提高强化学习的学习效率. 利用可测量数据, 自学习得到的运行指标能够保证生产指标优化, 并且限制在规定范围之内. 最后, 采用中国西部某大型选矿厂的实际数据进行仿真验证, 表明该方法的有效性.     

结合区块链技术的改进K-匿名激励机制方案

在基于位置服务中,K-匿名激励机制可以激励移动用户帮助其他用户实现K-匿名位置的隐私保护。然而,目前的K-匿名激励机制方案存在过度中心化、易单点失效、用户参与积极性不足等问题。当前,基于区块链的智能合约技术具有去中心化、安全性高、可验证等特性,可用来有效构建可编程金融,为解决K-匿名激励机制存在的问题提供了新思路。该方案结合区块链智能合约技术与改进的K-匿名激励算法,基于以太坊实验环境开发了K-匿名激励机制系统,将公有区块链中通用代币作为激励发放给参与用户,提出了一种可以提高参与用户积极性的保证金准入机制。相较于相关工作,改进后的激励算法在K-匿名组合生成方面节省了30%～40%的时间开销,该算法由智能合约实现,合约在区块链上自动执行,从而保证激励机制的安全性及可信性。     

Customer satisfaction incentives with budget constraints

We study the design of incentive contracts based on customer satisfaction (CS) surveys with reward budget limits. We extend principal‐agent models to consider budget constraints, survey response rates, and correlation between CS measure and demand. We derive the optimal incentive contract and study the impacts of these factors on contract performance. In contrast to the common belief that customer future values are the drivers of CS incentives, we show that CS incentives can benefit principals even in a single‐period setting where customers bring no future value. Improvements can be achieved without increasing total reward, because the CS incentive program reveals additional information about agents' service effort and diversifies their risk. Such effects are overlooked in existing CS research. With consideration of correlation between sales and CS measures, we provide a metrics selection rule regarding which reward(s)—CS, sales commission, or both—should be included in an incentive plan. We also study cumulative incentive schemes based on commonly used average CS measures and show that such incentive schemes may fail to motivate agents to increase service effort. Therefore, designing proper reward schemes is a critical issue for effective CS management and deserves future research.     

Securing one-way hash chain based incentive mechanism for vehicular ad hoc networks

One of the most promising applications of yet to come vehicular ad hoc networks (VANETs) is commercial advertising. However, in order to realize commercial advertising over VANET, proper incentives and security mechanisms must be taken into consideration due to the existence of selfish and/or malicious users in the real-world scenario. In this paper, we propose a secure incentive scheme for VANET advertising systems based on one-way hash chains. We also analyze the advertisement propagation behavior in our VANET advertising system using a mathematical model.     

Set reachability and set stability of Boolean networks with state-dependent asynchronous updating rule

Asynchronous behavior is significant for real biological systems. This paper explores the impact of state-dependent asynchronous updating rule (SDAUR) on the set reachability and set stability of Boolean networks (BNs). First, a set of state-dependent control variables is introduced to describe the SDAUR. Second, a new asynchronous set reachablity matrix is constructed based on an auxiliary input and semi-tensor product. Third, using the asynchronous set reachablity matrix, several necessary and sufficient conditions are obtained for the set reachablity and set stability of BNs with SDAUR. Finally, the new results proposed in this paper are verified through the immunomic network.     

异步复制流程的研究与性能改进

数据更新流程是远程复制系统的框架。针对不同的应用需求,系统可以采用不同的复制模式。文中主要讨论异步模式下的数据更新流程。在分析借鉴了已有的异步复制协议基础上,提出了一种改进性能的异步复制流程。原型实验表明,此数据更新流程的设计在保持数据的一致性以及系统简单、可靠性的同时,也降低了复制过程中对网络带宽的需求和I/O操作的数量。     

异步时钟下基于信息物理融合的水下潜器协同定位算法

在异步时钟下研究了一种基于信息物理融合的水下潜器协同定位问题.首先,构建了由浮标、传感器和潜器组成的水下信息物理融合系统架构.然后,考虑水下异步时钟影响,设计了基于传感器与潜器交互通信的异步定位策略,给出了潜器协同定位问题.为求解上述协同定位问题,分别提出了基于扩展卡尔曼滤波（Extended Kalman filter,EKF）与无迹卡尔曼滤波（Unscented Kalman filter,UKF）的水下潜器协同定位算法.最后,对上述定位算法的有界性以及克拉美罗下界（Cramér-Rao lower bound,CRLB）进行了分析.仿真结果表明,上述算法可有效消除异步时钟对水下定位的影响.同时基于无迹卡尔曼滤波的定位算法可提高定位精度.     

机会网络自私节点的Bertrand博弈与激励机制研究

在真实的网络环境中,很多节点可能是自私的,它们不愿意牺牲自己的资源为其他节点转发消息。针对这种情况,提出一种基于博弈论的激励机制,可以激励节点与其他节点相互合作。该机制为二阶段激励,激励节点接收消息以协助其他节点转发,同时激励节点转发更多的消息。把源节点与中继节点之间的竞争与合作模型化为Bertrand（伯特兰德）博弈,定义了源节点和中继节点的效用函数。求解了源节点的最佳定价策略和中继节点最佳的转发计划,验证了源节点与中继节点之间存在唯一的纳什均衡。模拟仿真结果表明提出的激励机制能够鼓励自私节点参与合作,能提高路由算法的传递率,同时降低了消息传递延迟。与基于声誉的激励机制相比,所提激励机制能使消息传递成功率提高31.4%、平均时延降低9.7%。     

Efficient Blockchain-Empowered Data Sharing Incentive Scheme for Internet of Things

In recent years, with many devices continuously joining the Internet of Things (IoT), data sharing as the main driver of the IoT market has become a research hotspot. However, the users are reluctant to participate in data sharing due to security concerns and lacking incentive mechanisms in the current IoT. In this context, blockchain is introduced into the data sharing of IoT to solve the trust problem of users and provide secure data storage. However, in the exploration of building a secure distributed data sharing system based on the blockchain, how to break the inherent performance bottleneck of blockchain is still a major challenge. For this reason, the efficient blockchain-based data sharing incentive scheme is studied for IoT. In the scheme, an efficient data sharing incentive framework based on blockchain is proposed, named ShareBC. Firstly, ShareBC uses sharding technology to build asynchronous consensus zones that can process data sharing transactions in parallel and deploy efficient consensus mechanisms on the cloud/edge servers and asynchronous consensus zones in sharding, thus improving the processing efficiency of data sharing transactions. Then, a sharing incentive mechanism based on a hierarchical data auction model implemented by a smart contract is presentedto encourage IoT users to participate in data sharing. The proposed mechanism can solve the problem of multi-layer data allocation involved in IoT data sharing and maximize the overall social welfare. Finally, the experimental results show that the proposed scheme is economically efficient, incentive-compatible, and real-time, with scalability, low cost, and good practicability.