考虑服务约束的第三方仓库收益与设计优化模型

doi:10.16381/j.cnki.issn1003-207x.2015.04.010

中国管理科学 ›› 2015, Vol. 23 ›› Issue (4): 78-85.doi: 10.16381/j.cnki.issn1003-207x.2015.04.010

考虑服务约束的第三方仓库收益与设计优化模型

徐浩轩^1,2, 龚业明^1,2,3, 袁哲^1,2, 张金隆^1,2,3

1. 华中科技大学管理学院, 湖北武汉 430074;
2. 华中科技大学现代管理信息研究中心, 湖北武汉 430074;
3. 武汉工商学院现代物流与商务湖北省协同创新中心, 湖北武汉 430065

收稿日期:2012-08-09 修回日期:2014-09-26 出版日期:2015-04-20 发布日期:2015-04-24
作者简介:徐浩轩(1989-), 男(汉族), 江西九江人, 华中科技大学管理学院, 博士研究生, 研究方向:库存管理、仓库管理.
基金资助:
国家自然科学基金资助项目(70901028,71271095)

A Design Model to Improve the Revenue of Third-party Warehouses with Service Constraints

XU Hao-xuan^1,2, GONG Ye-ming^1,2,3, YUAN Zhe^1,2, ZHANG Jin-long^1,2,3

1. School of Management, Huazhong University of Science & Technology, Wuhan 430074, China;
2. Modern Information Management Center at HUST, Wuhan 430074;
3. Collaborative Innovation Center for Modern Logistics and Business of Hubei, Wuhan Technology and Business University, Wuhan 430065, China

Received:2012-08-09 Revised:2014-09-26 Online:2015-04-20 Published:2015-04-24

摘要/Abstract

摘要： 第三方仓库作为服务提供商, 主要以期望收益最大化为目标, 但是必须满足一定的顾客服务标准。针对高需求环境, 考虑顾客服务水平约束, 提出了一个基于排队论的随机设计优化模型以使仓库的期望收益最大化。采用动态优化算法对模型求解, 选取实例进行了数值实验。结果显示, 模型的优化设计显著地提高了高需求环境下该第三方仓库的期望收益。在此基础上, 找到了服务约束的可行范围和有效范围, 为决策者制定服务标准提供了依据。

关键词: 设施设计与规划, 仓库管理, 第三方仓库, 服务约束

Abstract: As service providers, third-party warehouses mainly focus on increasing the expected revenue, but at the same time have to meet certain service standards. In a high demand environment, a stochastic design model based on queuing theory and taken into account of service constraint is preserted. The objective of the model is to maximize the expected long-run revenue. The problem is solved by dynamic programming and numerical experiments are conducted by using real data in a third-party warehouse. Finally, the results show that the new design in our method can improve the expected revenue of public storage warehouses with high demand and service constraints rate. Based on the result, the feasible and effective ranges of the service factor for decision-makers are further identified.

Key words: facility design and planning, warehouse management, third-party warehouse, service constraint

中图分类号:

F253

徐浩轩, 龚业明, 袁哲, 张金隆. 考虑服务约束的第三方仓库收益与设计优化模型[J]. 中国管理科学, 2015, 23(4): 78-85.

XU Hao-xuan, GONG Ye-ming, YUAN Zhe, ZHANG Jin-long. A Design Model to Improve the Revenue of Third-party Warehouses with Service Constraints[J]. Chinese Journal of Management Science, 2015, 23(4): 78-85.

参考文献

[1] Self Storage Association.Self storage industry fact sheet[R]. Alexandria, VA, USA, 2012.

[2] Self Storage Association UK.Annual industry report[R]. Cheshire, UK, 2009.

[3] De Koster R, Le-Duc T, Roodbergen K J. Design and control of warehouse order picking:A literature review [J]. European Journal of Operation Research, 2007, 182(2):481-501.

[4] Roach S S. Services under siege——the restructuring imperative [J]. Harvard Business Review, 1991, 69(5):82-91.

[5] Tompkins J A, White J A, Bozer Y A, et al. Facilities planning [M]. New York:John Wiley & Sons, 2003.

[6] Rao A K, Rao M R. Solution procedures for sizing of warehouses [J]. European Journal of Operation Research, 1998, 108(1):16-25.

[7] 邓爱民, 蔡佳, 毛浪.基于时间的自动化立体仓库货位优化模型研究[J]. 中国管理科学, 2013, 21(6):107-112.

[8] 朱杰, 周丽, 郭键. 分类存储人工拣选随机服务系统效率研究[J]. 管理科学学报, 2012, 15(2):59-71.

[9] Zhang Xiaodong, Gong Yeming, De Koster R, et al. Storage scheduling decision models for revenue management of self-storage warehouses[C]. Proceedings of 10th International TRAIL Congress, Netherlands, October, 2008, 14-15.

[10] Gong Yeming. Stochastic modelling and analysis of warehouse operations[D]. Rotterdam, Netherlands:Erasmus University, 2009.

[11] Talluri K T, Van Ryzin G J. The theory and practice of revenue management [M]. Boston:Kluwer, 2004.

[12] McGill J I, Van Ryzin G J. Revenue management:Research overview and prospects [J]. Transportation Science, 1999, 33(2):233-256.

[13] Chiang W-C, Chen J C H, Xu Xiaojing. An overview of research on revenue management:current issues and the future research [J]. International Journal of Revenue Management, 2007, 1(1):97-128.

[14] Bitran G R, Mondschein S V. An application of yield management to the hotel industry considering multiple say stays [J]. Operations Research, 1995, 43(3):427-443.

[15] Kjeldsen A H. Revenue management——theory and practice[D]. Lyngby, Denmark:DTU, 2005.

[16] Gronroos C. Service management and marketing [M]. New York:John Wiley & Sons, 2000.

[17] Bolton R N, Drew J H. A longitudinal analysis of the impact of service changes on customer attitudes [J]. Journal of Marketing, 1991, 55(1):1-9.

[18] Elliott T L. Maximizing revenue production while cutting costs:an airline industry mandate [J]. Journal of Revenue & Pricing Management, 2003, 1(4):355-368.

[19] Ladany S P. Optimal market segmentation of hotel rooms-the non-linear case [J]. Omega, 1996, 24(1):29-36

[20] Talluri K, Van Ryzin G. Revenue management under a general discrete choice model of consumer behavior [J]. Management Science, 2004, 50(1):15-33.

[21] Bertsimas D, Paschalidis Ioannis I C. Probabilistic service level guarantees in make-to-stock manufacturing systems [J]. Operations Research, 2001, 49(1):119-133.

[22] Bertsimas D, De Boer S. Simulation-based booking limits for airline revenue management [J]. Operations Research, 2005, 53(1):90-106.

[23] Tijms H C. A first course in stochastic models [M]. New York:John Wiley & Sons, 2003.

[24] Gross D, Harris C. Fundamentals of queuing theory [M]. New York:John Wiley & Sons, 1998.

[25] Cohen J W. On regenerative processes in queuing theory [M]. Berlin:Springer Verlag, 1976.

[26] Stoyan D. Comparison methods for queues and other stochastic models [M]. New York:John Wiley & Sons, 1983.

考虑服务约束的第三方仓库收益与设计优化模型

A Design Model to Improve the Revenue of Third-party Warehouses with Service Constraints

PDF (PC)

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 2

Metrics

本文评价

推荐阅读 10

[1]	赵宇哲, 周晶淼, 匡海波. 竞争环境下基于服务约束的轴-辐式海运网络优化研究[J]. 中国管理科学, 2016, 24(11): 47-57.
[2]	申成霖, 侯文华, 张新鑫, 卿志琼 . 基于信息更新与服务水平约束的供应链订货及协调决策[J]. 中国管理科学, 2012, 20(5): 55-63.