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Introduction

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Fuzzy Stochastic Optimization

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Abstract

Randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world. Randomness relates to the stochastic variability of all possible outcomes of a situation and can be perfectly and mathematically described by probability theory with random variable. Fuzziness, on the other hand, stems from the imprecision of subjective human knowledge and exists objectively with a variety of manifestations in numbers of situations such as data capture and process, blurred boundaries of the parameters, expertise applications, and lack of precise knowledge. Fuzzy variable in the context of theory of fuzzy set and possibility (see [114, 117, 118, 171, 172]) is widely accepted as an effective mathematical approach to model the fuzzy uncertainty.

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Notes

  1. 1.

    “Garbage In, Garbage Out” (abbreviated to GIGO) is a phrase in the fields of computer science and information communication technology. It is used primarily to call attention to the fact that computers will unquestioningly process the most nonsensical of input data and produce nonsensical output. It was popular in the early days of computing, but it applies even more today to describe failures in human decision making due to imprecise, incomplete, or faulty data (see [12]).

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    Shuming Wang & Junzo Watada

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Wang, S., Watada, J. (2012). Introduction. In: Fuzzy Stochastic Optimization. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-9560-5_1

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