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Mean-Risk Analysis of Single-Period Inventory Problems

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 178))

Abstract

In this chapter, we carry out mean-risk analysis for the single-period inventory problems. We first construct the basic inventory control model under the mean-risk framework. We then present two kinds of mean-risk objective functions and analytically prove the existence of an efficient region for either mean-risk model. After that, we explore the construction of the efficient frontier in the mean-risk domain. Before we conclude, numerical analysis is presented to illustrate the mean-risk trade-off in the single-period inventory decision making problems.

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Notes

  1. 1.

    To avoid confusion, we use exp( ) to represent exponent in this chapter.

  2. 2.

    Notice that the concavity of expected profit function is a standard result in the literature. The result on variance of profit is first proven by Chen and Federgruen (2000). Notice that when we incorporate the loss of goodwill opportunity cost of stockout, the variance of profit is no longer monotone (see Choi et al. 2008; Wu et al. 2009).

  3. 3.

    This utility function is similar to the ones employed by Lau (1980) and Choi et al. (2008).

References

  • Chen, F., & Federgruen, A. (2000). Mean-variance analysis of basic inventory models. Working paper, Columbia University.

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  • Choi, T. M., Li, D., & Yan, H. (2008). Mean-variance analysis for the newsvendor problem. IEEE Transactions on Systems, Man, and Cybernetics, Part A - Systems and Humans, 38, 1169–1180.

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  • Lau, H. S. (1980). The newsboy problem under alternative optimization objectives. Journal of the Operational Research Society, 31, 525–535.

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  • Wu, J., Li, J., Wang, S., & Cheng, T. C. E. (2009). Mean–variance analysis of the newsvendor model with stockout cost. Omega, 37, 724–730.

    Article  Google Scholar 

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Choi, TM., Chiu, CH. (2012). Mean-Risk Analysis of Single-Period Inventory Problems. In: Risk Analysis in Stochastic Supply Chains. International Series in Operations Research & Management Science, vol 178. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3869-4_2

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