基于供需网企业合作博弈模型的演化路径分析

传统企业间合作博弈问题的研究大都是基于合作策略和不合作策略两种情形展开,而与传统研究不同,本文在此基础上将企业间不合作策略细分为竞争策略和中立策略。以多功能开放型供需网企业为研究对象,运用演化博弈理论分析方法,通过构建供需网企业合作演化博弈模型,进而分析供需网企业合作过程中策略的选择以及博弈演化路径问题。研究结果表明:在长期的演化博弈过程中,企业策略的选择情形出现不稳定现象,即出现完全合作、完全不合作或者一方合作而另一方选择不合作策略的多种状态,其演化路径最终稳定于何种情形与模型的支付矩阵和初始参数设置有关。     

Marketing Strategy Formulation — Pure versus Mixed Strategies

The paper considers Kotler's competitive model and increases the number of possible marketing strategies available by taking into account the combinations of the strategy alternatives. From the larger set of marketing strategies, the optimal strategy or strategies is identified. The objective function of the firm is found to be satisfied better by the combined strategy rather than by the best strategy from the set used by Kotler. The optimal combined strategy is found by a heuristically optimizing SDRDYN-algorithm suitable to simulation studies. As is expected, the larger set of strategy alternatives considered enable the firm to increase the value of its objective function.     

两人进化博弈策略的决定机制与应用研究

通过建立一般情况下的两人进化博弈模型,给出了系统均衡点对应的矩阵行列式和迹表达式的经济含义,分析了16种典型情形下的进化稳定策略,详细讨论了均衡点稳定性分析结果所对应的博弈双方决策过程,从策略权衡的视角揭示了策略选择的内在机制。研究结果表明:不同策略前提下的相对净支付决定了系统的进化稳定策略,对方的策略选择以及自身可选策略的支付比较是影响博弈主体策略选择的两个基本要素,博弈主体会趋向于选择在对方策略既定下能够带来更大支付的策略。最后以环境治理中地方政府与企业以及地方政府之间的博弈关系为例,从对称博弈和非对称博弈两方面阐明了本文所构建模型在政策设计中的应用价值:针对不同案例,只要明确了两人博弈的支付矩阵,就可以通过计算相对净支付确定博弈双方的行为演化规律和稳定策略,从而简化计算过程,更加直接和更为便捷地为政策设计提供理论参考。     

沿海港口集装箱空箱调运策略优化模型

我国沿海港口进出口箱分布非常不均衡,由此产生了集装箱空箱调运现象,合理的空箱调运策略能够有效地降低航运成本。本文研究了沿海港口间的空箱调运问题。在传统确定目的港策略的基础上,提出了一种新的空箱调运策略,不确定目的港策略。针对两种不同调运策略分别建立了以总调运费用最小为目标的规划模型。并以中国沿海港口空箱调运为例,运用遗传算法,在不同的空箱供需情况下,对两种调运策略费用进行了优化求解。结果表明,供需平衡模式下,固定目的港策略略有优势;在供需不平衡模式中,不确定目的港策略优势更加明显。此研究能够为港口间空箱调运提供辅助决策。     

供应中断风险下制造商的后备采购与改善努力策略比较研究

在供应中断风险环境下,对制造商的后备采购策略和改善努力策略进行了比较分析.研究发现,制造商在改善努力策略时向主供应商的采购数量恒大于在后备采购策略时的采购数量.改善努力与后备采购策略的收益差总是随着改善努力成本投入的增大而呈现出递减的规律.当努力成本投入变得不经济时,制造商将放弃对主供应商的改善努力.     

Local design vs. global design: A strategic business choice

The market for a particular product consists of many customers having different needs and wants. A local design strategy attempts to increase market share and sales revenue by designing many variants of the product to exploit these differences. Such a strategy involves increased requirements for design, manufacturing, and marketing resources. A global design strategy offers a single product concept to all customers. Thus, the choice between a local design strategy and a global design strategy poses a fundamental tradeoff to the managers in many markets. Making such a decision is a complex process as it involves many design, manufacturing and marketing factors. We present a model based on optimal control theory representing major tradeoffs that exist between a local design strategy and a global design strategy. We demonstrate, through extensive computational experiments, how the model helps to gain strategic insight into the complex tradeoffs that exist between global design strategy and local design strategy alternatives under various scenarios over the life of a product.     

服务供应链视角下SaaS模式免费试用策略分析

针对处于市场推广期的SaaS模式中应用服务需求的不确定性,本文从服务供应链的视角对免费试用策略应对需求不确定性进行建模分析。设计了合作契约保证免费试用策略下服务供应链的协调;将免费试用策略绩效与传统的风险共担策略绩效作比较,得出免费试用策略的适用条件;通过数值分析验证了模型的有效性并得出了其管理学意义。研究表明,与风险共担策略相比,免费试用策略能够激励客户需求和有效规避SaaS模式中服务需求不确定性的风险,并提高服务供应链中各方收益;免费试用策略的适用性和绩效与应用服务提供商(ASP)技术能力水平有关;服务供应链协调可以使免费试用取得更好的效果。     

Does the Balanced Scorecard make a difference to the strategy development process?

A great number of strategy tools are being taught in strategic management modules. These tools are available to managers for use in facilitating strategic decision making and enhancing the strategy development process in their organisations. A number of studies have been published examining which are the most popular tools; however there is little empirical evidence on how their utilisation influences the strategy process. This paper is based on a large scale international survey on the strategy development process, and seeks to examine the impact of a particular strategy tool, the Balanced Scorecard (BSC), upon the strategy process. Recently, it has been suggested that as a strategy tool, the BSC can influence all elements of the strategy process. The results of this study indicate that although there are significant differences in some elements of the strategy process between the organisations that have implemented the BSC and those that have not, the impact is not comprehensive.     

Tournament Competition and its Merits for Coevolutionary Algorithms

In a competitive coevolutionary algorithm, the competition strategy, selecting opposing individuals, has a great influence on the performance of the algorithm. Therefore, a good competition strategy is crucial for an effective and efficient competitive coevolutionary algorithm. In this paper, we propose a new competition strategy called tournament competition. We investigate its characteristics and merits when applied to adversarial problems. To verify the performance of the new strategy, we first classify adversarial problems into two types: solution-test problems and game problems. We apply the strategy to both types. A set of experiments compares our strategy to several existing competition strategies and analyzes several aspects such as solution quality, evolution speed, and coevolutionary balance. The experimental results indicate that some of the existing competition strategies give different patterns according to problem types. The results also support that the proposed tournament strategy has the potential for finding good solutions, regardless of problem types.     

购买价格递减的在线租赁问题策略设计

运用在线问题与竞争分析的方法研究了购买价格递减的在线租赁问题。通过揭示相关费用函数的性质,先后给出了最优离线策略以及在线策略。通过竞争比分析,证明了我们给出的在线策略是该问题唯一最优策略,而且该策略的竞争比随购买价格的优惠率的增加呈严格递减趋势。竞争分析结果表明考虑购买价格递减因素能够改进在线策略的竞争比从而提高决策效率。     

An examination of HMM‐based investment strategies for asset allocation

We develop and analyse investment strategies relying on hidden Markov model approaches. In particular, we use filtering techniques to aid an investor in his decision to allocate all of his investment fund to either growth or value stocks at a given time. As this allows the investor to switch between growth and value stocks, we call this first strategy a switching investment strategy. This switching strategy is compared with the strategies of purely investing in growth or value stocks by tracking the quarterly terminal wealth of a hypothetical portfolio for each strategy. Using the data sets on Russell 3000 growth index and Russell 3000 value index compiled by Russell Investment Services for the period 1995–2008, we find that the overall risk‐adjusted performance of the switching strategy is better than that of solely investing in either one of the indices. We also consider a second strategy referred to as a mixed investment strategy which enables the investor to allocate an optimal proportion of his investment between growth and value stocks given a level of risk aversion. Numerical demonstrations are provided using the same data sets on Russell 3000 growth and value indices. The switching investment strategy yields the best or second best Sharpe ratio as compared with those obtained from the pure index strategies and mixed strategy in 14 intervals. The performance of the mixed investment strategy under the HMM setting is also compared with that of the classical mean–variance approach. To make the comparison valid, we choose the same level of risk aversion for each set‐up. Our findings show that the mixed investment strategy within the HMM framework gives higher Sharpe ratios in 5 intervals of the time series than that given by the standard mean–variance approach. The calculated weights through time from the strategy incorporating the HMM set‐up are more stable. A simulation analysis further shows a higher performance stability of the HMM strategies compared with the pure strategies and the mean–variance strategy. Copyright © 2009 John Wiley & Sons, Ltd.     

基于在线理论的股票算法交易策略研究

运用在线理论研究多支股票算法交易策略。在El-Yaniv等人研究基础上,构造了单支股票买入问题的在线策略,证明该策略为最优在线策略;将构造的单支股票交易策略应用到多支股票交易策略问题中,设计了多支股票交易策略算法,并以每支股票收益加权进行投资组合;最后选择上证A股二十支股票从2009年到2012年的交易时间价格数据验证本文所提策略有效性。将20支股票随机抽取10支组成一组,选4组分别进行验证,结果表明本文所给策略对于任意选择的多支股票有较好收益。对交易周期分别选取10个偶数长度进行验证,发现交易周期为18天时平均收益最大,平均收益率为5.2%。     

Charge depleting range dynamic strategy with power feedback considering fuel-cell degradation

A charge depleting range dynamic strategy considering the fuel-cell degradation is proposed for the plug-in fuel cell hybrid electric vehicles in this paper, to seek the excellent economy performance with various driving ranges. The proposed strategy is developed by means of incorporating an adaptive equivalent factor into equivalent consumption minimization strategy with power feedback control. Firstly, the mathematical modeling of the proposed strategy is formulated to adjust the equivalent factor corresponding to the battery state of charge, which may vary with the forthcoming trip distance to dominate the expected energy consumption. The fuel cell voltage decay rate is applied to the feedback control of the restricted fuel-cell power, which is designed as the degradation model of fuel cell and integrated with the strategy. Secondly, the realization process of the charge depleting range dynamic strategy with restricted power feedback control model is a new attempt to design the real-time control method. Finally, the proposed strategy is validated by a numerical model developed by using the MATLAB/Simulink software and its effectiveness was evaluated by comparing it with the equivalent consumption minimization strategy. A sensitivity analysis is also conducted to study the effects of different trip distances. The effectiveness of power feedback control in fuel cell durability is validated through a hardware-in-the-loop experiment. The verified results demonstrate the influence of the equivalent factor on the control process, which makes the proposed strategy possible to provide significant improvement in the economy performance and fuel-cell durability.     

On the optimal design of insurance contracts with guarantees

The paper analyzes insurance contracts where the benefits of the insured depend on the performance of an investment strategy and which guarantee a certain interest rate on the contributions made by the insured. The insured has to decide simultaneously on the investment strategy and the guarantee scheme. For a CRRA insured and in a BS economy, the optimal combination is given by a constant mix strategy and the contribution guarantee scheme. In case the insured has a subsistence level, the CPPI strategy turns out to be optimal for arbitrary schemes. We illustrate our results by numerical examples and analyze the utility losses of a CRRA insured due to the use of a suboptimal combination of investment strategy and guarantee scheme.     

Time-dependent reliability-based design optimization with probabilistic and interval uncertainties

Time-dependent reliability-based design optimization with both probabilistic and interval uncertainties is a cost-consuming problem in engineering practice which generally needs huge computational burden. In order to deal with this issue, a sequential single-loop optimization strategy is established in this work. The established sequential single-loop optimization strategy converts the original triple-loop optimization into a sequence of deterministic optimization, the estimations of time instant and interval value that corresponding to the worst case scenario, and the minimum performance target point searching. Two key points in the sequential single-loop optimization strategy guarantee the high efficiency of the proposed strategy. One is that no iterative searching step is needed to find the minimum performance target point at each iteration in the proposed sequential single-loop optimization strategy. The other is that only the correction step needs the reliability analysis to correct the design parameter solutions. In the example section, four minimum performance target point searching techniques are combined with the sequential single-loop optimization strategy to solve the corresponding optimization problems so to illustrate the effectiveness of the established strategy.     

连续对策的最大熵策略密度对策解

对于正方形[0,2]×[0,2]上的连续对策,将局中人的非纯策略(概率分布函数)的导数称为这个局中人的策略密度(概率密度函数).建立了这种连续对策的最大熵理论.主要证明了当每个局中人都没有最优纯策略时,具有最大熵的最优策略密度集合的非空紧凸性,研究了最优策略密度的最大熵,给出一类带有最大熵的连续对策.     

基于风险补偿模型的耐用设备占线租赁策略研究

传统的占线优化理论没有考虑到风险因素,其本质是一种无风险策略,具有一定的局限性,然而在现实中更多的人愿意利用风险来获得额外收益。基于此,本文结合交易费用与现实租赁市场中二手市场存在的情形,研究了耐用设备占线租赁的风险回报模型。风险回报模型是对最优确定性策略的拓展,且概率型预期风险回报模型是对确定型预期风险回报模型的拓展。通过数据分析表明风险回报模型能够有效地提高策略性能,从而使决策者可以根据自己的风险容忍度和预期选择最优的租赁策略。     

无标底招标项目中招投标各方的博弈研究

在无标底招标项目中,招投标各方之间存在诸多博弈现象.本文根据项目管理和博弈的方法,对投标方的投标策略和支付函数进行了深入的分析.同时,利用价值效益评价决策的方法建立了招标方的评标计分模型和中标评价模型,并根据招标方的评标偏好性,提出了招标方的评标策略集和中标策略集.最后,对招投标双方的多种博弈现象进行了讨论,提出了双方的纳什均衡策略和不同条件下的双方最优中标策略和最优投标策略.     

A velocity observer design for tracking task-based motions of unicycle type mobile robots

The paper presents a design of a nonlinear velocity observer and its application within a model-based tracking control strategy for tracking task-based motions of unicycle type mobile robots. The strategy is the model reference tracking control strategy for programmed motion and it enables switching between controllers employed in it to improve a tracking precision as well as switching between coordinates used for modeling based on a type of a nonholonomic system. The strategy benefits by adding the velocity observer to its architecture due to the reduction of a number of measurements needed for feedback tracking.     

B2C零售商退货渠道策略研究

基于全渠道环境下,考虑B2C零售商提供全额退款保证,建立了同渠道退货策略和全渠道退货策略下的博弈模型,研究B2C零售商的退货渠道策略选择问题。结果表明,全渠道退货策略下,B2C零售商总是会实施高价策略,且当消费者线上退货损失较大时,最优定价随着消费者线上退货损失递增,反之递减;当B2C零售商实体店退货产品处理成本较小时,全渠道退货策略能有效增加消费者需求,实施全渠道退货策略是占优的;从消费者的角度看,当产品匹配率和消费者线上退货损失较高时,B2C零售商将会实施全渠道退货策略。