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Modelling stochastic decision systems using dependent-chance programming
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DOI：10.1016/0377-2217(95)00371-1.png)
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Abstract
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This paper further discusses the techniques of dependent-chance programming, dependent-chance multiobjective programming and dependent-chance goal programming. Some illustrative examples are provided to show how to model complex stochastic decision systems by using dependent-chance programming and how to serve these models by employing a Monte Carlo simulation based genetic algorithm. (C) 1997 Elsevier Science B.V.
Keywords:
stochastic programming
goal programming
multiobjective programming
dependent-chance programming
genetic algorithm
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