通胀市场下多设备租赁的在线策略分析

doi:10.16381/j.cnki.issn1003-207x.2016.02.009

中国管理科学 ›› 2016, Vol. 24 ›› Issue (2): 69-75.doi: 10.16381/j.cnki.issn1003-207x.2016.02.009

通胀市场下多设备租赁的在线策略分析

徐维军¹, 刘幼珠¹, 陈晓丽¹, 胡茂林², 高丽³

1. 华南理工大学工商管理学院, 广东广州 510641;
2. 淮阴师范学院数学科学学院, 江苏淮安 223300;
3. 华南理工大学数学学院, 广东广州 510641

收稿日期:2013-12-15 修回日期:2015-03-11 出版日期:2016-02-20 发布日期:2016-02-25
通讯作者: 徐维军 E-mail:xuwj@scut.edu.cn
作者简介:徐维军(1975-),男(汉族),宁夏人,华南理工大学工商管理学院研究员,研究方向:在线金融算法,E-mail:xuwj@scut.edu.cn.
基金资助:
国家自然科学基金资助青年项目(71471065);中央高校基本科研业务费专项资金资助(2012ZZ0035);中央高校基本科研业务费自然科学类项目(x21xD214183W)

Competitive Strategy for On-line Multiple Devices Leasing in an Inflation Market

XU Wei-jun¹, LIU You-zhu¹, CHEN Xiao-li¹, HU Mao-lin², GAO Li³

1. School of Business Administration, South China University of Technology, Guangzhou 510641, China;
2. School of Mathematical Science, Huaiyin Normal University, Huaian 223300, China;
3. School of Mathematics, South China University of Technology, Guangzhou 510641, China

Received:2013-12-15 Revised:2015-03-11 Online:2016-02-20 Published:2016-02-25

摘要/Abstract

摘要： 现实租赁市场中,企业同时租赁多台设备的现象大量存在,但经营者面临的最大难题是如何对这多台设备进行在线租赁的组合优化,从而降低决策成本,而通货膨胀又进一步增加了决策难度。本文运用在线算法和竞争分析法建立多设备投资的风险控制策略,并分析通胀对决策的影响。首先在Karp经典模型上给出通胀因素下多设备投资的最优在线和离线策略;接着建立设备租赁在连续可分情形下的最优风险控制模型,进一步结合实际投资中设备必须以离散整数租赁的特点,对CR策略进行调整和优化,得到近似的CRJ策略,使得策略更符合实际投资活动。最后给出具体实例分析,结果显示,当物价指数逐渐增大时,最优决策日期相应提前,对应最优策略的竞争比也逐渐增大,进一步说明物价指数因素和多设备投资因素的引入对投资者的决策有着重要的影响,为多设备在线租赁问题的研究提供了新的解决思路。

关键词: 通货膨胀, 多设备租赁, 在线算法, 竞争分析

Abstract: There exist massive phenomena of leasing multiple devices at the same time in the real leasing market. And the biggest problem what the manager faces is to optimize the combination of multiple devices on-line leasing in order to reduce the decision-making cost. However, inflation further increases the difficulty. In this paper, risk control model for the multiple devices leasing problem is put forward using the method of on-line algorithm and competitive analysis, and the impact of inflation on decision-making is analyzed. Firstly, the on-line and off-line strategies are proposed respectively for the multiple devices leasing according to the model of Karp's with the factor of inflation. Then to improve the competitive ratio in Karp's model, the risk control strategy which we call the CR strategy is discussed in theory with the hypothesis that the device is continuous separability. Furthermore, when consider that the number of devices investing in real decision-making must be integer, the risk control model is reconstructed and optimized to gain a new approximate strategy-CRJ strategy. Finally, the optimal competitive performance of the strategy is discussed and illustrated by numerical analysis, which shows that the competitive performance of on-line strategy is affected by the fact of inflation and the ways of investing. More, a new idea in multiple devices leasing problem is given in this paper.

Key words: inflation, multiple devices leasing, on-line algorithm, competitive analysis

中图分类号:

F224

徐维军, 刘幼珠, 陈晓丽, 胡茂林, 高丽. 通胀市场下多设备租赁的在线策略分析[J]. 中国管理科学, 2016, 24(2): 69-75.

XU Wei-jun, LIU You-zhu, CHEN Xiao-li, HU Mao-lin, GAO Li. Competitive Strategy for On-line Multiple Devices Leasing in an Inflation Market[J]. Chinese Journal of Management Science, 2016, 24(2): 69-75.

参考文献

[1] Bell T J, Thomas J. Tax benefits of leasing[J]. Economics Letters, 2013, 120(2):338-341.

[2] Aurora C, Bontas B. Lease financing:A new dual approach[J]. Management Strategies Journal, 2013, 23:87-96.

[3] Sule O E, Amuni S I.Equipment leasing as a source of finance for small and medium scale entrepreneurs in Nigeria[J]. International Journal of Management Excellence, 2014, 2(3):247-256.

[4] Karp R. On-line algorithms versus off-line algorithms:How much is it worth to know the future?//Proceedings of IEIP 12th Word Computer Congress. Madrid Spain,September, 1992,7-11.

[5] El-Yaniv R, Knaiel R, Linial N. Competitive optimal on-line leasing[J]. Algorithmica, 1999, 25:116-140.

[6] Al-Binali S. A risk-reward framework for the competitive analysis of financial games[J]. Algorithmica, 1999, 25(1):99-115.

[7] Irani S, Ramanatham D. The problem of renting versus buying[J]. Personal Communication, 1998,4(3):6-11.

[8] Bienkowski M. Price fluctuations:To buy or to rent[M]//Bampis E,Jansen K.Approximation and Online Algorithms Berlin Heiderlbery, 2010:25-36.

[9] Ding Lili, Liu Xinmin, Kang Wanglin. Competitive analysis of online price discount replacement problem//Proleedings of International Joint Conference on Computational Sciences and Optimization, Sanya,Hainan,April,24-26,2009.

[10] 王杨, 董玉成, 徐寅峰,等. 多阶段占线赁购问题与竞争分析[J]. 中国管理科学, 2009, 17(3):101-106.

[11] Lotker Z, Patt-Shamir B, Rawitz D. Ski rental with two general options[J]. Information Processing Letters, 2008, 108(6):365-368.

[12] Lotker Z, Patt-Shamir B, Rawitz D.Rent. Lease or buy:Randomized algorithms for multislope ski rental//Proceedings of the 25th Annual Symposium on Theoretical Aspects of Computer Science, Bordeaux,France,February,2008,21-23.

[13] Fujiwara H, Kitano T, Fujito T. On the best possible competitive ratio for multislope ski rental[M]//Asano T,Nakano S,Okamoto Y,et al. Algorithms and Computation, Behin Heidelbery:Springer,2011:544-553.

[14] 辛春林, 陈剑, 刘天亮. 基于凸情形下在线设备更新问题的竞争分析[J]. 系统工程理论与实践, 2009, 29(11):145-151.

[15] 张永, 张卫国, 徐维军. 在线设备更新问题的竞争策略及其风险补偿模型[J]. 中国管理科学, 2010, 18(2):113-119.

[16] 徐维军, 胡茂林. 基于物价指数上涨的最优在线租赁决策模型[J]. 系统工程理论与实践, 2013, 33(3):1-10.

[17] 刘幼珠, 徐维军, 胡茂林. 通胀市场下的风险补偿在线租赁策略设计[J]. 运筹与管理, 2013, 22(4):175-181.

[18] Yang Xingyu, Zhang Weiguo, Zhang Yong, et al. Optimal randomized algorithm for a generalized ski-rental with interest rate[J]. Information Processing Letters, 2012, 112(13):548-551.

[19] Khanafer A, Kodialam M, Puttaswamy K. The constrained ski-rental problem and its application to online cloud cost optimization//Proceedings of 2013 IEEE INFOCOM, Turin,April 14-19,2013:1492-1500.

[20] Epstein L, Zebedat-Haider H. Rent or buy problem with a fixed time horizon[M]//Chatterjee K,Sgall J. Mathematical Foundations of Computer Science 2013, Berlin Heidelbery:Springer,2013:361-372.

[21] 杨兴雨, 张卫国, 徐维军,等. 基于绩效比和合同约束的多阶段在线租赁[J]. 中国管理科学, 2014, 22(2):94-100.

[22] 胡茂林. 可分资产的在线租赁策略及其竞争分析[J]. 系统工程理论与实践, 2011, 31(1):144-150.

[23] 胡茂林, 徐维军, 刘幼珠. 存在市场利率的连续松弛多重在线租赁问题[J]. 管理科学学报, 2014, 17(9):29-39.

[24] El-Yaniv R, Fiat A, Karp R, et al. Optimal search and one-way trading online algorithms[J]. Algorithmica, 2001, 30(1):101-139.

通胀市场下多设备租赁的在线策略分析

Competitive Strategy for On-line Multiple Devices Leasing in an Inflation Market

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