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

  • * Corresponding author: Xingyu Yang

    * Corresponding author: Xingyu Yang 
Abstract Full Text(HTML) Figure(5) / Table(3) Related Papers Cited by
  • 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.

    Mathematics Subject Classification: Primary: 90B05, 68W27; Secondary: 68W40.

    Citation:

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  • 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 2.  Comparison of daily cumulative gain without shortage cost

    Figure 3.  Comparison of daily cumulative gain with shortage cost

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

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

    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
     | Show Table
    DownLoad: CSV

    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
     | Show Table
    DownLoad: CSV

    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
     | Show Table
    DownLoad: CSV
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