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Gains and costs of informationin stochastic programming

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Abstract

The paper reviews the role of sensors as a variable depicting information in a stochasticprogram. Through examples, and with mathematical analysis of random measures, it isshown how policy variables affect the sensors in a given problem. Sensors are amenable tomathematical derivations. It is shown how the trade‐off between the gain from introducingnew information into the problem, and the cost of that action, can be addressed. Suggestionsfor further investigation are offered.

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  1. Zvi Artstein
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Artstein, Z. Gains and costs of informationin stochastic programming. Annals of Operations Research 85, 129–152 (1999). https://doi.org/10.1023/A:1018913609464

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