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Journal of the Operations Research Society of Japan
We propose a minirnax model with a "quadratic" recourse. In stochastic linear programming models, a decision maker has been assumed to know the probability distribution of random variables. Here we consider the case that the parameters of distribution are unknown. We impose the restrictions on the unknown parameters from the view point of a confidence region, and then seek a minimax solution that minimizes the worst case of the parameters. This model reflects the situation minimizing thedoi:10.15807/jorsj.30.218 fatcat:qjvfg5hrfvf3hegzu4eozod3zy