供应商歧视定价下网络零售商店内推介策略研究

研究了供应商歧视定价时网络零售商店内推介策略。首先,以供应商统一定价模型为基准,通过逆推归纳法求解不同推介策略组合下零售商和供应商的均衡利润,研究发现:仅当消费者对两家零售商认知差异较小时四种推介策略组合才能同时成立,且随着推介费用的增大两零售商均衡推介策略依次为:都不推介、仅强势零售商1推介和双向推介。其次,构建供应商歧视定价模型,发现歧视定价有利于弱势零售商2获得市场空间,随着消费者对两家零售商感知差异和推介费用的变化呈现出多样化的均衡推介策略。最后,探讨了两种定价模型下供应商的最优利润,发现受推介策略的影响歧视定价未必能够为供应商带来更多利润。     

碳交易机制下资金约束制造商替代产品的最优生产策略研究

碳交易机制和资金约束在很大程度上影响企业的生产决策,但很少有文献研究碳排放和资金双约束下企业对普通与低碳两种替代品生产决策问题。因此,本文在碳交易机制下讨论了资金约束下制造商两种产品的生产决策问题。本文采用基于有无碳交易和银行融资划分四种情形,基于报童模型构建优化模型分析制造商的最优决策。研究发现:(1)无融资情形下,如果制造商的初始资金很少,则制造商生产更多的普通产品;如果制造商的初始资金很多,则制造商生产更多的低碳产品;(2)在银行融资情形下,当利率较小时,制造商生产更多的低碳产品;当利率较大时,制造商生产更多的普通产品;(3)在银行融资情形下,如果碳排放配额较大,无碳交易机制时的融资量和融资成本高于有碳交易机制时的融资量和融资成本;如果碳排放配额较低则结论相反。     

Dynamic routing in open queueing networks: Brownian models,cut constraints and resource pooling

We present an introductory review of recent work on the control of open queueing networks. We assume that customers of different types arrive at a network and pass through the system via one of several possible routes; the set of routes available to a customer depends on its type. A route through the network is an ordered set of service stations: a customer queues for service at each station on its route and then leaves the system. The two methods of control we consider are the routing of customers through the network, and the sequencing of service at the stations, and our aim is to minimize the number of customers in the system. We concentrate especially on the insights which can be obtained from heavy traffic analysis, and in particular from Harrison's Brownian network models. Our main conclusion is that in many respects dynamic routingsimplifies the behaviour of networks, and that under good control policies it may well be possible to model the aggregate behaviour of a network quite straightforwardly.Supported by SERC grant GR/F 94194.     

Globally and Superlinearly Convergent QP-Free Algorithm for Nonlinear Constrained Optimization

A new, infeasible QP-free algorithm for nonlinear constrained optimization problems is proposed. The algorithm is based on a continuously differentiable exact penalty function and on active-set strategy. After a finite number of iterations, the algorithm requires only the solution of two linear systems at each iteration. We prove that the algorithm is globally convergent toward the KKT points and that, if the second-order sufficiency condition and the strict complementarity condition hold, then the rate of convergence is superlinear or even quadratic. Moreover, we incorporate two automatic adjustment rules for the choice of the penalty parameter and make use of an approximated direction as derivative of the merit function so that only first-order derivatives of the objective and constraint functions are used.     

Markov games with incomplete information

We consider zero-sum Markov games with incomplete information. Here, the second player is never informed about the current state of the underlying Markov chain. The existence of a value and of optimal strategies for both players is shown. In particular, we present finite algorithms for computing optimal strategies for the informed and uninformed player. The algorithms are based on linear programming results.     

On a student-related optimal control problem

In a recent paper (Ref. 1), Cheng and Teo discussed some further extensions of a student-related optimal control problem which was originally proposed by Raggettet al. (Ref. 2) and later on modified by Parlar (Ref. 3). In this paper, we treat further extensions of the problem.This paper is a modified and improved version of Ref. 4. It is based, in part, on research sponsored by NSF.     

保险赔付中的最优对冲策略

本文对带有付费过程$A_t$的保险公司在金融市场$(S_t,Q_t,B_t)$上通过购买股票$S_t$、兑换外币$Q_t$以及购买无风险资产$B_t$的投资过程而采取的最优投资策略, 使保险公司所面临的风险最小进行探讨. 利用Galtchouk-Kunita-Watanabe分解定理将风险表达式重新表达, 从而找到保险公司所能采取的风险最小的最优对冲策略. 文中举出一个具有现实性意义的例子将文章的重要结论加以应用, 使本文更具有应用价值.     

On differential games with Markov perfect triggering

This paper is an attempt to throw some light on the issue of whether defining history-dependent state variables in a differential game does allow for a dynamic play of precommitment equilibria. We suggest the application of trigger strategies in a state-feedback context. Based on a punishment mode in Markov perfect strategies and being able to detect even past deviations followed by histories returning to equilibrium, these subgame-perfect strategies lead to the enforcement of certain outcomes by means of dynamic rules of strategic interaction. The last part of our exposition is devoted to specific game structures under which a trigger equilibrium can be used as well as a punishment mode.     

Evolutionary games

This paper deals with a mathematical game. As the name implies, the game concept is formulated with biological evolution in mind. An evolutionary game differs from the usual game concepts in that the players cannot choose their strategies. Rather, the strategies used by the players are handed down from generation to generation. It is the survival characteristics of a strategy that determine the outcome of the evolutionary game. Players interact and receive payoffs according to the strategies they are using. These interactions, in turn, determine the fitness of players using a given strategy. The survival characteristics of strategy are determined directly from the fitness functions. Necessary conditions for determining an evolutionarily stable strategy are developed here for a continuous game. Results are illustrated with an example.Dedicated to G. LeitmannThis work was supported by NSF Grant No. INT-82-10803 and The University of Western Australia (Visiting Fellowship, Department of Mathematics, 1983).     

An evasion game with a destination

This paper solves an aiming and evasion game in which a gunner with a number of shots attempts to hit an evader moving along the positivex-axis. The gunner's aiming of the evader is complicated by the fact that there is a delay due to the time taken for the shot to reach the evader from the gunner.