Abstract
Abstract Sometimes a complex stochastic decision system undertakes multiple tasks called events, and the decision-maker wishes to maximize the chance functions which are defined as the probabilities of satisfying these events. Originally introduced by Liu and Iwamura [B. Liu, K. Iwamura, Modelling stochastic decision systems using dependent-chance programming, European Journal of Operational Research 101 (1997) 193–203], dependent-chance programming is aimed at maximizing some chance functions of events in an uncertain environment. In this work, we show that the original dependent chance-programming framework needs to be extended in order to capture an exact reliability measure for a given plan.
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