Abstract
Stochastic programming has been used since the late 1950s for decision models where input data (coefficients in LP problems) have been given probability distributions. The pioneer works were done by Dantzig [47], Beale [9], Tintner [247], Simon [223], Charnes, Cooper and Symonds [39], and Charnes and Cooper [40]. Since then, a number of stochastic programming models have been formulated in inventory theory, system maintenance, micro-economics, and banking and finance. The most recent summaries of the development of stochastic programming methods are Stancu-Minasian [BM48] and Wets [260].
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© 1992 Springer-Verlag Berlin Heidelberg
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Lai, YJ., Hwang, CL. (1992). Possibilistic Programming. In: Fuzzy Mathematical Programming. Lecture Notes in Economics and Mathematical Systems, vol 394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48753-8_4
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DOI: https://doi.org/10.1007/978-3-642-48753-8_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-56098-2
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