基于Stackelberg博弈的协作网络功率分配策略

针对协作网络中的功率分配问题,提出基于Stackelberg博弈的分配策略。首先建立博弈模型,源节点根据中继节点分配的功率给出价格;中继节点根据自身资源情况、信道状态、位置信息以及源节点提出的价格,进行协作传输功率的分配,从而构建用户效用函数;接着证明了该效用函数满足凹函数的条件,且存在均衡点,因此参与决策的用户可以通过求解协作功率和价格的Stackelberg均衡解(SE)最大化自己的效用;最后,通过仿真实验验证了均衡点的存在,并对源节点位置不同情况下节点的价格、功率和效用进行了分析,实验中离中继更近的源节点的协作功率和效用分别是距离较远用户的1.29倍和1.37倍。理论分析与实验结果证明了策略的有效性,而且该策略能适用于协作网络及其他分布式网络。     

纵向产品差异的闭环供应链定价策略研究

为了解决闭环供应链中的定价策略问题,根据单一制造商和单一零售商构成的二级闭环供应链系统,应用博弈理论研究新产品与再造品之间存在纵向产品差异时闭环供应链中制造商和零售商的定价策略。得出了一个合作博弈的均衡解（合作决策）和一个非合作博弈（均衡解斯坦克尔伯格）的均衡解（分散决策）,并对两种定价策略作了进一步的比较,得出了一些有价值的结论。     

基于囚徒困境策略的改进HK网络上的合作博弈

为模拟现实世界的合作行为,本文在HK网络模型基础上提出了一种具有高聚类幂律可调性质的新的网络模型,并分析了囚徒困境博弈在此网络上的演化。通过仿真实验,研究了该网络的高聚类特性对合作行为的影响。大量实验表明,网络的高聚类特性可以极大促进合作现象的涌现。同时研究也发现,随着诱惑参数的变大,合作水平也会随之下降,但幅度不大。总之,该演化博弈模型可以促进合作现象的涌现并抵御背叛策略的传播。     

基于Stackelberg博弈的共享储能容量优化与商业模式研究

本文围绕我国能源结构转型面临的系能源大量投入使用所需规模化储能资源支撑的挑战,紧扣新时代战略发展方向,对新型储能商业模式进行研究。我国能源结构转型面临挑战——大量使用新型能源需要规模化储能资源的支撑,本文紧扣新时代战略发展方向,对新型储能商业模式进行了研究。研究了基于新能源互补的共享储能商业运营模式,实现了共享储能设备与新能源发电功率互济,并基于Stackelberg主从博弈方法对共享储能设备租赁进行定价,以实现了用户、储能商、电力公司多方利益的最大化。以用户侧储能为研究对象,建立了基于全寿命周期的储能容量优化配置模型,考虑具有短期用电需求的峰值型用户,提出了基于共享理念的储能合作社商业模式。最后通过算例及现场试验验证了所提出的共享储能商业模式的可行性。     

Incentive equilibrium in bioresource sharing problem

A dynamic game model of bioresource management problem is considered. The center (referee) which shares a reservoir, and the players (countries) which harvest the fish stock on their territory are the participants of this game. In this paper we investigate the new type of equilibrium—cooperative incentive equilibrium. The equilibria are constructed in the case, when the players punish each other for a deviation from the cooperative equilibrium, and in the case, when the center punishes them for a deviation. Some results of the numerical modelling are given.     

Playing seriously – How gamification and social cues influence bank customers to use gamified e-business applications

The development of business applications with game features has given rise to a new trend called gamification and challenged e-banking to introduce new game elements, such as mechanics and social cues, to its traditional applications. Yet, there has been a lack of empirical evidence regarding the intention to use, these type of applications and their possible impacts on business. Here, we explore the role of gamification, socialness, and other four well-known variables (ease-of-use, usefulness, enjoyment, and intention to use) in a gamified business application and corresponding business. We proposed and evaluated a model based on the Technology Acceptance Model to better analyze and understand the adoption of gamified business applications. To test this model, we developed a study using a sample of 183 bank customers, and we found that gamification significantly improved the customer’s sense of social interaction, which, in turn, strongly influenced the customer’s intention to use the applications. We argue that this intention to use could provide a strong benefit to the business, in term of increased customer engagement. This paper presents a new conceptual model to predict behavioral intention in regards to gamification in e-banking, illustrating seven variables that affect the adoption of e-banking by bank customers. Our findings contribute overall to a better understanding of gamification in e-banking (with the extension of Technology Acceptance Model theories, and the new variable gamification), providing important practical implications for software development and marketing practices.     

基于模糊回收价格的逆向供应链定价策略研究

在由单一制造商和单一零售商构成的逆向供应链系统中，回收产品质量的不确定性导致回收价格的不确定性．针对这种不确定性，将回收价格看作三角模糊数，应用模糊理论和博弈理论对回收价格浮动的基准点进行决策，分别得出了两个非合作博弈的均衡解（斯坦克尔伯格均衡和纳什均衡）和一个合作博弈的均衡解（联合定价），并给出了各均衡条件下制造商和零售商各自回收价格的浮动范围．     

考虑处理基金和回收品质量的闭环供应链决策

为解决废弃电子产品处理基金政策和回收品质量不确定性对闭环供应链决策及协调的影响问题,运用博弈论和MATLAB数值仿真的方法,构建合作与非合作决策博弈模型,研究了两种情况下处理基金和回收品质量对销售及回收价格、批发价格、回收数量、供应链节点企业及整体利润的影响。结果表明,处理基金能够以价格形式传递到消费者,并提高销售价格、回收价格、回收数量和供应链整体利润;回收品质量提升对批发价格和销售价格无影响,但能增加回收数量和供应链利润;合作决策比非合作决策对企业、消费者及生态保护都更有利;价格契约和利润分享机制结合可以有效实现供应链协调。     

基于批发价格事前和事后决策的供应链合作促销策略研究

针对单一供应商和单一零售商组成的二级供应链系统,构建了批发价格事前和事后决策下的合作促销模型,探讨了批发价格事前和事后决策对合作促销的影响,并求得Stackelber主从博弈下的均衡合作促销策略。研究结果表明,在批发价格事前决策且零售商努力影响需求、或批发价格事后决策且供应商努力影响需求的情形下,合作促销均不是一个有效的激励策略;在批发价格事前决策且供应商努力影响需求的情形下,只有当促销努力成本共担系数小于一定的阈值时,合作促销才是一个有效的激励策略;在批发价格事后决策且零售商努力影响需求的情形下,合作促销始终是有效的激励策略。最后通过算例分析验证了上述结论的有效性。     

一种基于合作博弈论的自动驾驶车道变更模型

提出一个新颖的车道变更模型,采用合作博弈方法激励车辆参与合作.首次将合作博弈理论应用到车道变更领域,设计用于两车变道的纳什讨价还价变道模型,然后扩展为三车的合作博弈变道模型,并求出变道模型的纳什讨价还价解和夏普利值.为了进一步激励车辆参与合作,在收益分配方案中加入支付补偿部分来实现整体收益的可转移性,从而取得模型的解....     

考虑消费者环保意识的WEEE 双渠道回收模型

在考虑消费者环保意识的基础上,建立基于不同消费者群体行为的WEEE双渠道回收模型,采用博弈论比较两条渠道在竞争情形与合作情形下的决策.研究表明,在不同的市场环境下,消费者的环保意识以及环保消费者的比例对两条渠道的合作策略有不同程度的影响.当两条渠道相互合作时,供应链的利润随着普通消费者环保意识的增加而增大,随环保消费者比例的增大而减小.在一般情况下,两条渠道合作时的回收价格和回收量小于竞争情形时的回收量和回收价格,但网络回收平台的单位期望收益远大于流动商贩的单位期望收益的情形除外.当消费者的环保意识、环保消费者的比例以及两条渠道的回收产品的单位利润满足一定条件时,双方合作才会对整个回收产业起到积极作用.最后,对模型中的各参数进行了敏感性分析,并用算例验证了模型的有效性.     

INFLUENCE OF ENVIRONMENTAL CHANGES ON COOPERATIVE BEHAVIOR IN THE PRISONER'S DILEMMA GAME ON AN ARTIFICIAL SOCIAL MODEL

In this paper, by simulations on an artificial social model, we analyze cooperative behavior of agents playing the prisoner's dilemma game, in which each of the agents has the two strategies: cooperate and defect. Because defect yields a better payoff whichever strategy an opponent chooses, it is rational for an agent to choose defect in a single game or a finite number of games. However, it is known that a pair of cooperates can also be a Nash equilibrium pair if the players do not know when the game is over or the game is infinitely repeated. To investigate such cooperative behavior, we employ an artificial social model called the Sugarscape and carry out simulations on the model. Arranging three kinds of environments in the Sugarscape, we examine cooperative behavior of agents who are essentially selfish, in a sense that they maximize their payoffs, and investigate influence of environmental changes on the cooperative behavior.     

On oligopoly spectrum allocation game in cognitive radio networks with capacity constraints

Dynamic spectrum sharing is a promising technology to improve spectrum utilization in future wireless networks. The flexible spectrum management provides new opportunities for licensed primary user and unlicensed secondary users to reallocate the spectrum resource efficiently. In this paper, we present an oligopoly pricing framework for dynamic spectrum allocation in which the primary users sell excessive spectrum to the secondary users for monetary return. We present two approaches, the strict constraints (type-I) and the QoS penalty (type-II), to model the realistic situation that the primary users have limited capacities. In the oligopoly model with strict constraints, we propose a low-complexity searching method to obtain the Nash Equilibrium and prove its uniqueness. When reduced to a duopoly game, we analytically show the interesting gaps in the leader–follower pricing strategy. In the QoS penalty based oligopoly model, a novel variable transformation method is developed to derive the unique Nash Equilibrium. When the market information is limited, we provide three myopically optimal algorithms “StrictBEST”, “StrictBR” and “QoSBEST” that enable price adjustment for duopoly primary users based on the Best Response Function (BRF) and the bounded rationality (BR) principles. Numerical results validate the effectiveness of our analysis and demonstrate the convergence of “StrictBEST” as well as “QoSBEST” to the Nash Equilibrium. For the “StrictBR” algorithm, we reveal the chaotic behaviors of dynamic price adaptation in response to the learning rates.     

Cost minimization in utility computing systems

Utility computing is a form of computer service whereby the company providing the service charges the users for using the system resources. In this paper, we present system‐optimal and user‐optimal price‐based job allocation schemes for utility computing systems whose objective is to minimize the cost for the users. The system‐optimal scheme provides an allocation of jobs to the computing resources that minimizes the overall cost for executing all the jobs in the system. The user‐optimal scheme provides an allocation that minimizes the cost for individual users in the system for providing fairness. The system‐optimal scheme is formulated as a constraint minimization problem, and the user‐optimal scheme is formulated as a non‐cooperative game. The prices charged by the computing resource owners for executing the users jobs are obtained using a pricing model based on a non‐cooperative bargaining game theory framework. The performance of the studied job allocation schemes is evaluated using simulations with various system loads and configurations. Copyright © 2012 John Wiley & Sons, Ltd.     

基于服务协作中间件的动态流程模型

新兴的面向服务体系结构正在加速软件的发展和变化,无法适应动态环境的应用将逐渐失去作用,尤其对那些面临着需求频繁变更的业务流程管理系统而言更是如此.为了响应这种现实需求,基于Web服务和业务流程管理技术,提出了服务协作中间件(service cooperation middleware,简称SCM)模型,探讨了其内部机理与协作流程元模型的形式化.通过引入模型转换,扩充流程状态空间,定义了动态流程模型,动态流程的结构重构和行为自适应可以借助SCM的反射能力得以实现.针对SCM模型,设计了流程虚拟机(prrocess virtual machine,简称PVM),流程在运行时由PVM控制执行.借助于模型驱动机制,业务流程可从设计到运行不断地进行模型变换.由此建立的业务流程能够更灵活、更广泛地适用于各种开放环境,提升企业分布计算.     

Analysis of a simple capacity game

We study a two‐player two‐fare‐class static single‐period capacity allocation game with complete information. Nonnested (partitioned) booking limit policies are investigated in both noncooperative and cooperative situations. We show the existence of unique Nash equilibrium in the noncooperative situation. In the cooperative game, we analyze the cost saving of the two players and investigate the concavity of the objective function. For both noncooperative and cooperative settings, we assume the demands to be a truncated normal distribution and provide a comprehensive sensitivity analysis to discover the effects of unit revenue, rejection cost, and transfer rate on the equilibrium solution. Our numerical experiments show that the nonnested model can be a good approximation to the nested booking limit model. For the cooperative setting, we identify conditions that give rise to improvements in the total system revenue. Finally, under each game‐theoretic setting, we present the managerial implications of our solutions along with numerical examples.     

Dynamic agent based simulation of welfare effects of urban disasters

An agent based model for assessing the welfare impacts of urban disasters is presented. This couples a population allocation algorithm with a simulation platform. The fully articulated model fuses both bottom-up (locational choice for workplace, residence and daily activities) and top-down (land use and housing price) protocols. This study moves beyond current research by addressing economic welfare consequences of urban disasters. The resilience capabilities of different income groups are identified. This is illustrated for the Jerusalem central business district. Empirical results at the micro-scale suggest that physical destruction leads to a zero-sum game within the housing market in which wealthier residents hold an advantage over the poor. This results in the transformation of neighborhoods and displacement of poor and vulnerable populations. Low income groups lose both physical ground and the social support systems that go with location. Policy implications of these findings are discussed.     

Does it matter with whom you slay? The effects of competition,cooperation and relationship type among video game players

Cooperation and competition have emerged as factors that may affect video game players. Competition consistently has been found to elicit increased aggression whilst cooperation has been found to mitigate aggression and increase cooperative behaviors after game play. Of interest is the effect of the relationship between players (friend vs. stranger) in cooperative and competitive multiplayer contexts. In this study, we considered how game goal structure – competition or cooperation – and relationships between players – friend or stranger – affect aggression and cooperative behaviors. Compared with competition, cooperative play resulted in significantly more cooperative behaviors in a modified Prisoner’s Dilemma task. However, neither competitive nor cooperative goal structures significantly increased state hostility, suggesting that altering players’ gaming goals (e.g. competition or cooperation) may not be enough to elicit strong affective aggression. Additionally, cooperative game play was found to predict increased cooperative behaviors and trust in their partner. Implications of the findings are discussed.     

Fuzzy restrictions and an application to cooperative games with restricted cooperation

The concept of restriction, which is an extension of that of interior operator, was introduced to model limited cooperation in cooperative game theory. In this paper, a fuzzy version of restrictions is presented. We show that these new operators, called fuzzy restrictions, can be characterized by the transitivity of the fuzzy dependence relations that they induce. As an application, we introduce cooperative games with fuzzy restriction, which are used to model cooperative situations in which each player in a coalition has a level of cooperation within the coalition. A value for these games is defined and characterized.     

智能仓储货位规划与AGV路径规划协同优化算法

智能仓储的优化一般分为货架优化和路径优化两部分.货架优化针对货物与货架两者的关系,对货物摆放位置进行优化;而路径优化主要寻找自动引导小车（Automated Guided Vehicle,AGV）的最优路径规划.目前,大多的智能仓储优化仅对这两部分进行独立研究,在实际仓储应用中只能以线性叠加的方式解决问题,导致问题的求解易陷入局部最优中.本文通过对智能仓储环节中各部分的关系进行耦合分析,提出了货位和AGV路径协同优化数学模型,将货架优化和路径规划归为一个整体;此外,提出了智能仓储协同优化框架的求解算法,包括货品相似度求解算法和改进的路径规划算法;并在以上两种算法的基础上,使用改进的遗传算法,实现了货位路径协同优化.实验结果验证了本文提出的智能仓储协同优化算法的有效性和稳定性.通过使用该算法可有效提高仓储的出货效率,降低运输成本.