INCORPORATING SAFETY-FIRST CONSTRAINTS IN LINEAR PROGRAMMING PRODUCTION MODELS

A recent survey indicated that many procedures view risk in a safety-first context. Traditional methods used to impose safety-first constraints in optimization models have often been difficult to implement. This is particularly true when endogenous decisions affect the distribution of the chance-constrained random variable. This paper presents a method whereby probabilistic constraints can be easily imposed upon finitely discrete random variables. The procedure uses a linear version of the lower partial moment stochastic inequality. The resulting solutions are somewhat conservative but are less so than the results using the previously published mean income-absolute deviation stochastic inequality.


Issue Date:
1988-07
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/32152
Published in:
Western Journal of Agricultural Economics, Volume 13, Number 1
Page range:
29-36
Total Pages:
8




 Record created 2017-04-01, last modified 2017-08-24

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