American Institute of Mathematical Sciences

Advanced
  • Previous Article
    A class of descent four–term extension of the Dai–Liao conjugate gradient method based on the scaled memoryless BFGS update
  • JIMO Home
  • This Issue
  • Next Article
    Parametric solutions to the regulator-conjugate matrix equations
April  2017, 13(2): 633-647. doi: 10.3934/jimo.2016037

Distribution-free solutions to the extended multi-period newsboy problem

Yong Zhang 1, , Xingyu Yang 1,, and  Baixun Li 2,

1. 

School of Management, Guangdong University of Technology, Guangzhou 510520, China
2. 

School of Business Administration, Guangdong University of Finance & Economics, Guangzhou 510320, China

* Corresponding author: Xingyu Yang

Received  March 2015 Revised  December 2015 Published  May 2016

This paper concerns the distribution-free, multi-period newsboy problem in which the newsboy has to decide the order quantity of the newspaper in the subsequent period without knowing the distribution of the demand. The Weak Aggregating Algorithm (WAA) developed in learning and prediction with expert advices makes decision only based on historical information and provides theoretical guarantee for the decision-making method. Based on the advantage of WAA and stationary expert advices, this paper continues providing distribution-free methods for the extended multi-period newsboy problems in which the shortage cost and the integral order quantities are considered. In particular, we provide an alternative proof for the theoretical result which guarantees the cumulative gain our proposed method achieves is as large as that of the best stationary expert advice. Numerical examples are provided to illustrate the effectiveness of our proposed methods.

Keywords: Multi-period newsboy problem, shortage cost, integral order quantity, distribution-free solution, weak aggregating algorithm.
Mathematics Subject Classification: Primary: 90B05, 68W27; Secondary: 68W40.
Citation: Yong Zhang, Xingyu Yang, Baixun Li. Distribution-free solutions to the extended multi-period newsboy problem. Journal of Industrial & Management Optimization, 2017, 13 (2) : 633-647. doi: 10.3934/jimo.2016037
References:
[1]

S. Al-Binali, A risk-reward framework for the competitive analysis of financial games, Algorithmica, 25 (1999), 99-115.  doi: 10.1007/PL00009285.  Google Scholar

[2]

H. K. Alfares and H. H. Elmorra, The distribution-free newsboy problem: extension to the shortage penalty case, International Journal of Production Economics, 93-94 (2005), 465-477.  doi: 10.1016/j.ijpe.2004.06.043.  Google Scholar

[3]

O. Besbes and A. Muharremoglu, On implications of demand censoring in the newsvendor problem, Management Science, 59 (2013), 1407-1424.   Google Scholar

[4]

A. Burnetas and C. Smith, Adaptive ordering and pricing for perishable products, Operations Research, 48 (2000), 436-443.  doi: 10.1287/opre.48.3.436.12437.  Google Scholar

[5]

N. Cesa-Bianchi and G. Lugosi, Prediction, Learning, and Games, Cambridge University Press, Cambridge, 2006. doi: 10.1017/CBO9780511546921.  Google Scholar

[6]

L. L. Ding, X. M. Liu and Y. F. Xu, Competitive risk management for online Bahncard problem, Journal of Industrial and Management Optimization, 6 (2010), 1-14.  doi: 10.3934/jimo.2010.6.1.  Google Scholar

[7]

G. Gallego and I. Moon, The distribution free newsboy problem: review and extensions, Journal of the Operational Research Society, 44 (1993), 825-834.  doi: 10.2307/2583894.  Google Scholar

[8]

W. T. Huh, R. Levi, P. Rusmevichientong and J. B. Orlin, Adaptive data-driven inventory control with censored demand based on Kaplan-Meier estimator, Operations Research, 59 (2011), 929-941.  doi: 10.1287/opre.1100.0906.  Google Scholar

[9]

W. T. Huh and P. Rusmevichientong, A non-parametric asymptotic analysis of inventory planning with censored demand, Mathematics of Operations Research, 34 (2009), 103-123.  doi: 10.1287/moor.1080.0355.  Google Scholar

[10]

Y. Kalnishkan and M. V. Vyugin, The weak aggregating algorithm and weak mixability, Journal of Computer and System Sciences, 74 (2008), 1228-1244.  doi: 10.1016/j.jcss.2007.08.003.  Google Scholar

[11]

M. Keisuke, The multi-period newsboy problem, European Journal of Operational Research, 171 (2006), 170-188.  doi: 10.1016/j.ejor.2004.08.030.  Google Scholar

[12]

S. Kunnumkal and H. Topaloglu, Using stochastic approximation methods to compute optimal base-stock levels in inventory inventory control problems, Operations Research, 56 (2008), 646-664.  doi: 10.1287/opre.1070.0477.  Google Scholar

[13]

S. Kunnumkal and H. Topaloglu, A stochastic approximation method for the single-leg revenue management problem with discrete demand distributions, Mathematical Methods of Operations Research, 70 (2009), 477-504.  doi: 10.1007/s00186-008-0278-x.  Google Scholar

[14]

T. Levina, Y. Levin, J. McGill, M. Nediak and V. Vovk, Weak aggregating algorithm for the distribution-free perishable inventory problem, Operations Research Letters, 38 (2010), 516-521.  doi: 10.1016/j.orl.2010.09.006.  Google Scholar

[15]

X. Lu, J. Song and K. Zhu, Analysis of perishable-inventory systems with censored demand data, Operations Research, 56 (2008), 1034-1038.  doi: 10.1287/opre.1080.0553.  Google Scholar

[16]

I. Moon and S. Choi, Distribution free newsboy problem with balking, Journal of the Operational Research Society, 46 (1995), 537-542.   Google Scholar

[17]

I. Moon and S. Choi, Distribution free procedures for make-to-order (MTO), make-in-advance (MIA), and composite policies, International Journal of Production Economics, 48 (1997), 21-28.  doi: 10.1016/S0925-5273(96)00026-6.  Google Scholar

[18]

I. Moon and E. A. Silver, The multi-item newsvendor problem with a budget constraint and fixed ordering costs, Journal of the Operational Research Society, 51 (2000), 602-608.   Google Scholar

[19]

G. R. Murray and E. A. Silver, A Bayesian analysis of the style goods inventory problem, Management Science, 12 (1996), 785-797.  doi: 10.1287/mnsc.12.11.785.  Google Scholar

[20]

H. Scarf, A min-max solution of an inventory problem, in: K. Arrow, S. Karlin, H. Scarf (Eds.), Studies in The Mathematical Theory of Inventory and Production, Stanford University Press, California, (1958), 201–209. Google Scholar

[21]

H. Scarf, Bayes solution of the statistical inventory problem, Annals of Mathematical Statistics, 30 (1959), 490-508.  doi: 10.1214/aoms/1177706264.  Google Scholar

[22]

G. L. Vairaktarakis, Robust multi-item newsboy models with abudget constraint, International Journal of Production Economics, 66 (2000), 213-226.   Google Scholar

[23]

Y. Zhang, V. Vovk and W. G Zhang, Probability-free solutions to the non-stationary newsvendor problem, Annals of Operation Research, 223 (2014), 433-449.  doi: 10.1007/s10479-014-1620-8.  Google Scholar

show all references

References:
[1]

S. Al-Binali, A risk-reward framework for the competitive analysis of financial games, Algorithmica, 25 (1999), 99-115.  doi: 10.1007/PL00009285.  Google Scholar

[2]

H. K. Alfares and H. H. Elmorra, The distribution-free newsboy problem: extension to the shortage penalty case, International Journal of Production Economics, 93-94 (2005), 465-477.  doi: 10.1016/j.ijpe.2004.06.043.  Google Scholar

[3]

O. Besbes and A. Muharremoglu, On implications of demand censoring in the newsvendor problem, Management Science, 59 (2013), 1407-1424.   Google Scholar

[4]

A. Burnetas and C. Smith, Adaptive ordering and pricing for perishable products, Operations Research, 48 (2000), 436-443.  doi: 10.1287/opre.48.3.436.12437.  Google Scholar

[5]

N. Cesa-Bianchi and G. Lugosi, Prediction, Learning, and Games, Cambridge University Press, Cambridge, 2006. doi: 10.1017/CBO9780511546921.  Google Scholar

[6]

L. L. Ding, X. M. Liu and Y. F. Xu, Competitive risk management for online Bahncard problem, Journal of Industrial and Management Optimization, 6 (2010), 1-14.  doi: 10.3934/jimo.2010.6.1.  Google Scholar

[7]

G. Gallego and I. Moon, The distribution free newsboy problem: review and extensions, Journal of the Operational Research Society, 44 (1993), 825-834.  doi: 10.2307/2583894.  Google Scholar

[8]

W. T. Huh, R. Levi, P. Rusmevichientong and J. B. Orlin, Adaptive data-driven inventory control with censored demand based on Kaplan-Meier estimator, Operations Research, 59 (2011), 929-941.  doi: 10.1287/opre.1100.0906.  Google Scholar

[9]

W. T. Huh and P. Rusmevichientong, A non-parametric asymptotic analysis of inventory planning with censored demand, Mathematics of Operations Research, 34 (2009), 103-123.  doi: 10.1287/moor.1080.0355.  Google Scholar

[10]

Y. Kalnishkan and M. V. Vyugin, The weak aggregating algorithm and weak mixability, Journal of Computer and System Sciences, 74 (2008), 1228-1244.  doi: 10.1016/j.jcss.2007.08.003.  Google Scholar

[11]

M. Keisuke, The multi-period newsboy problem, European Journal of Operational Research, 171 (2006), 170-188.  doi: 10.1016/j.ejor.2004.08.030.  Google Scholar

[12]

S. Kunnumkal and H. Topaloglu, Using stochastic approximation methods to compute optimal base-stock levels in inventory inventory control problems, Operations Research, 56 (2008), 646-664.  doi: 10.1287/opre.1070.0477.  Google Scholar

[13]

S. Kunnumkal and H. Topaloglu, A stochastic approximation method for the single-leg revenue management problem with discrete demand distributions, Mathematical Methods of Operations Research, 70 (2009), 477-504.  doi: 10.1007/s00186-008-0278-x.  Google Scholar

[14]

T. Levina, Y. Levin, J. McGill, M. Nediak and V. Vovk, Weak aggregating algorithm for the distribution-free perishable inventory problem, Operations Research Letters, 38 (2010), 516-521.  doi: 10.1016/j.orl.2010.09.006.  Google Scholar

[15]

X. Lu, J. Song and K. Zhu, Analysis of perishable-inventory systems with censored demand data, Operations Research, 56 (2008), 1034-1038.  doi: 10.1287/opre.1080.0553.  Google Scholar

[16]

I. Moon and S. Choi, Distribution free newsboy problem with balking, Journal of the Operational Research Society, 46 (1995), 537-542.   Google Scholar

[17]

I. Moon and S. Choi, Distribution free procedures for make-to-order (MTO), make-in-advance (MIA), and composite policies, International Journal of Production Economics, 48 (1997), 21-28.  doi: 10.1016/S0925-5273(96)00026-6.  Google Scholar

[18]

I. Moon and E. A. Silver, The multi-item newsvendor problem with a budget constraint and fixed ordering costs, Journal of the Operational Research Society, 51 (2000), 602-608.   Google Scholar

[19]

G. R. Murray and E. A. Silver, A Bayesian analysis of the style goods inventory problem, Management Science, 12 (1996), 785-797.  doi: 10.1287/mnsc.12.11.785.  Google Scholar

[20]

H. Scarf, A min-max solution of an inventory problem, in: K. Arrow, S. Karlin, H. Scarf (Eds.), Studies in The Mathematical Theory of Inventory and Production, Stanford University Press, California, (1958), 201–209. Google Scholar

[21]

H. Scarf, Bayes solution of the statistical inventory problem, Annals of Mathematical Statistics, 30 (1959), 490-508.  doi: 10.1214/aoms/1177706264.  Google Scholar

[22]

G. L. Vairaktarakis, Robust multi-item newsboy models with abudget constraint, International Journal of Production Economics, 66 (2000), 213-226.   Google Scholar

[23]

Y. Zhang, V. Vovk and W. G Zhang, Probability-free solutions to the non-stationary newsvendor problem, Annals of Operation Research, 223 (2014), 433-449.  doi: 10.1007/s10479-014-1620-8.  Google Scholar

Figure 1.  The gain function for Levina et al.'s multi-period newsboy problem with salvage. The slope of the graph is $p-c$ to the left of $y=d$ and $s-c$ to the right of $y=d$
Figure Options

Download full-size image

Download as PowerPoint slide

Figure 2.  Comparison of daily cumulative gain without shortage cost
Figure Options

Download full-size image

Download as PowerPoint slide

Figure 3.  Comparison of daily cumulative gain with shortage cost
Figure Options

Download full-size image

Download as PowerPoint slide

Figure 4.  Comparison between daily cumulative gain of DAS and ANS for trial 1
Figure Options

Download full-size image

Download as PowerPoint slide

Figure 5.  Comparison between daily cumulative gain of DAS and ANS for trial 2
Figure Options

Download full-size image

Download as PowerPoint slide

Table 1.  Cumulative gains of DAS and experts without/with shortage cost
$N$ 100 200 300 400
DAS 3864/3721 6843/6211 9978/8928 12672/11339
$\theta=1$ 1520/-1966 3040/-3218 4560/-4568 6080/-5582
$\theta=2$ 2635/325 5093/1089 7678/1952 10187/3033
$\theta=3$ 3497/2223 6489/4375 9531/6507 12396/8700
$\theta=4$ 3955/3493 6923/6167 10068/9018 12733/11459
$\theta=5$ 3780/3780 6269/6269 8936/8936 10995/10995
Ratios 0.977/0.984 0.988/0.986 0.991/0.990 0.995/0.989
Table Options

Download as excel

$N$ 100 200 300 400
DAS 3864/3721 6843/6211 9978/8928 12672/11339
$\theta=1$ 1520/-1966 3040/-3218 4560/-4568 6080/-5582
$\theta=2$ 2635/325 5093/1089 7678/1952 10187/3033
$\theta=3$ 3497/2223 6489/4375 9531/6507 12396/8700
$\theta=4$ 3955/3493 6923/6167 10068/9018 12733/11459
$\theta=5$ 3780/3780 6269/6269 8936/8936 10995/10995
Ratios 0.977/0.984 0.988/0.986 0.991/0.990 0.995/0.989
Table 2.  AVEs and STDs of Ratios of cumulative gains of DAS and best expert without/with shortage cost
TN 10 20 30 40
AVE 0.9861/0.9917 0.9821/0.9904 0.9802/0.9905 0.9800/0.9910
STD 0.0152/0.0041 0.0135/0.0035 0.0147/0.0037 0.0148/0.0034
Table Options

Download as excel

TN 10 20 30 40
AVE 0.9861/0.9917 0.9821/0.9904 0.9802/0.9905 0.9800/0.9910
STD 0.0152/0.0041 0.0135/0.0035 0.0147/0.0037 0.0148/0.0034
Table 3.  Comparison between cumulative gains of DAS and ANS without shortage cost
trial 1 2 3 4 5 6 7 8 9 10
DAS 235 110 164 185 153 227 158 188 196 150
ANS 241 106 159 180 151 211 153 183 192 147
Table Options

Download as excel

trial 1 2 3 4 5 6 7 8 9 10
DAS 235 110 164 185 153 227 158 188 196 150
ANS 241 106 159 180 151 211 153 183 192 147
[1]

Zongwei Chen. An online-decision algorithm for the multi-period bank clearing problem. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021091
[2]

I-Lin Wang, Shiou-Jie Lin. A network simplex algorithm for solving the minimum distribution cost problem. Journal of Industrial & Management Optimization, 2009, 5 (4) : 929-950. doi: 10.3934/jimo.2009.5.929
[3]

Zhiping Chen, Jia Liu, Gang Li. Time consistent policy of multi-period mean-variance problem in stochastic markets. Journal of Industrial & Management Optimization, 2016, 12 (1) : 229-249. doi: 10.3934/jimo.2016.12.229
[4]

Lin Jiang, Song Wang. Robust multi-period and multi-objective portfolio selection. Journal of Industrial & Management Optimization, 2021, 17 (2) : 695-709. doi: 10.3934/jimo.2019130
[5]

Lihua Bian, Zhongfei Li, Haixiang Yao. Time-consistent strategy for a multi-period mean-variance asset-liability management problem with stochastic interest rate. Journal of Industrial & Management Optimization, 2021, 17 (3) : 1383-1410. doi: 10.3934/jimo.2020026
[6]

Hongguang Ma, Xiang Li. Multi-period hazardous waste collection planning with consideration of risk stability. Journal of Industrial & Management Optimization, 2021, 17 (1) : 393-408. doi: 10.3934/jimo.2019117
[7]

Christina Burt, Louis Caccetta, Leon Fouché, Palitha Welgama. An MILP approach to multi-location, multi-period equipment selection for surface mining with case studies. Journal of Industrial & Management Optimization, 2016, 12 (2) : 403-430. doi: 10.3934/jimo.2016.12.403
[8]

Lan Yi, Zhongfei Li, Duan Li. Multi-period portfolio selection for asset-liability management with uncertain investment horizon. Journal of Industrial & Management Optimization, 2008, 4 (3) : 535-552. doi: 10.3934/jimo.2008.4.535
[9]

Zhen Wang, Sanyang Liu. Multi-period mean-variance portfolio selection with fixed and proportional transaction costs. Journal of Industrial & Management Optimization, 2013, 9 (3) : 643-656. doi: 10.3934/jimo.2013.9.643
[10]

Ning Zhang. A symmetric Gauss-Seidel based method for a class of multi-period mean-variance portfolio selection problems. Journal of Industrial & Management Optimization, 2020, 16 (2) : 991-1008. doi: 10.3934/jimo.2018189
[11]

Hideaki Takagi. Extension of Littlewood's rule to the multi-period static revenue management model with standby customers. Journal of Industrial & Management Optimization, 2021, 17 (4) : 2181-2202. doi: 10.3934/jimo.2020064
[12]

Chuangwei Lin, Li Zeng, Huiling Wu. Multi-period portfolio optimization in a defined contribution pension plan during the decumulation phase. Journal of Industrial & Management Optimization, 2019, 15 (1) : 401-427. doi: 10.3934/jimo.2018059
[13]

Yan Zhou, Chi Kin Chan, Kar Hung Wong. The impacts of retailers' regret aversion on a random multi-period supply chain network. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021086
[14]

Toyohiko Aiki. On the existence of a weak solution to a free boundary problem for a model of a shape memory alloy spring. Discrete & Continuous Dynamical Systems - S, 2012, 5 (1) : 1-13. doi: 10.3934/dcdss.2012.5.1
[15]

Zhenhua Guo, Zilai Li. Global existence of weak solution to the free boundary problem for compressible Navier-Stokes. Kinetic & Related Models, 2016, 9 (1) : 75-103. doi: 10.3934/krm.2016.9.75
[16]

Xianping Wu, Xun Li, Zhongfei Li. A mean-field formulation for multi-period asset-liability mean-variance portfolio selection with probability constraints. Journal of Industrial & Management Optimization, 2018, 14 (1) : 249-265. doi: 10.3934/jimo.2017045
[17]

Huiling Wu, Xiuguo Wang, Yuanyuan Liu, Li Zeng. Multi-period optimal investment choice post-retirement with inter-temporal restrictions in a defined contribution pension plan. Journal of Industrial & Management Optimization, 2020, 16 (6) : 2857-2890. doi: 10.3934/jimo.2019084
[18]

Cong Qin, Xinfu Chen. A new weak solution to an optimal stopping problem. Discrete & Continuous Dynamical Systems - B, 2020, 25 (12) : 4823-4837. doi: 10.3934/dcdsb.2020128
[19]

Tong Li, Anthony Suen. Existence of intermediate weak solution to the equations of multi-dimensional chemotaxis systems. Discrete & Continuous Dynamical Systems, 2016, 36 (2) : 861-875. doi: 10.3934/dcds.2016.36.861
[20]

Tien-Yu Lin, Bhaba R. Sarker, Chien-Jui Lin. An optimal setup cost reduction and lot size for economic production quantity model with imperfect quality and quantity discounts. Journal of Industrial & Management Optimization, 2021, 17 (1) : 467-484. doi: 10.3934/jimo.2020043

2019 Impact Factor: 1.366

Tools

Metrics

  • PDF downloads (115)
  • HTML views (415)
  • Cited by (2)

Other articles
by authors

[Back to Top]

Copyright © 2021 American Institute of Mathematical Sciences