【作者】 邹怿；

【导师】 高莹；

【作者基本信息】 东北大学 ， 金融学， 2007， 硕士

【摘要】 近年来,随着计算机网络技术及银行间支付清算体系的不断发展与进步,银行业务也随之发生了革命性的变革,银行的经营网点已从砖墙式建筑向ATM、POS等网络支付体系转移,银行卡及其服务已成为各大商业银行及存款机构的重要产品和核心业务。银行卡运营网络状况的好坏,在银行的经营管理当中占有举足轻重的地位。因此,为了保持银行卡网络正常的运行,银行应当在实现收益最大、抗风险能力最强的前提下为银行卡网络分配适当的资金,以满足网络内银行卡的资金需求,这是当前银行管理者迫切需要解决的难题。本文将中国银联网络环境下的银行卡资金分配问题作为本文的研究对象,以中国银联网络内银行卡不确定的资金需求为切入点,对中国银联网络环境下银行卡资金的分配问题进行了初步研究。本文通过对中国银联网络下银行卡资金需求的分解与分析,使用仿真——优化混合情景生成算法生成银行卡资金需求情景矩阵,结合鲁棒优化的思想建立了中国银联网络资金分配鲁棒优化模型。在此基础之上,文章结合中国银联网络的实际环境,运用SPSS13.0对仿真的情景进行聚类,得到了一个两阶段五个情景的情景树。使用这一情景树描述网络内不确定的资金需求,并运用MATLAB7.1的遗传算法与优化工具箱求解模型,讨论了在不同模型鲁棒性权重下,对网络系统总收益、总收益方差和需求偏离值平方和的影响,验证了鲁棒优化模型抗扰动、稳定性与可靠性高的特点。更多还原

【Abstract】 In recent years, a revolutionary change has happened in the bank services following by the continual development and improvement of computer networks and inter-bank payment and cleaning system. The service network of banks has transferred from physical infrastructures to network payment systems such as ATM and POS. Bankcards and their services have become the important products and central business. The operation conditions of bankcard network play an important role in the management of banks. Thus, banks should allocate proper fund for the bankcard network to maintain its daily operation in the preconditions of realizing the maximal returns and anti-risk ability and satisfy the fund demands of bankcards in the network, which is the urgent problems to be solved by bankers.It has been considered in this dissertation that the fund allocation problem in the environment of China UnionPay network. The dissertation takes the uncertain fund demand of China UnionPay network as a breaking point and carries on a preliminary research on it. According to the decomposition and analysis of fund demand of bankcards in the China UnionPay network, the dissertation makes use of simulation-and-optimization-based hybrid scenario generation algorithm to generate the fund demand scenario matrices of bankcards and establishes the robust optimization model for fund allocation of China UnionPay network. On the foundation of this, the dissertation clusters the scenarios generated from simulation with the help of SPSS 13.0 and obtains a two stage scenario trees of five scenarios. The uncertain fund demands in the network are described by the scenario trees. Moreover, the genetic algorithm and optimization toolboxes of MATLAB 7.1 are used for solving the model. It has been discussed that the influences of different model robust weights on total return of network system, variance of total return of network system and square sum of demand departures in the paper. Furthermore, the anti-jamming features, stability and reliability of the robust optimization model are verified.更多还原