In this paper, an optimization problem with uncertain objective function coefficients is considered. The uncertainty is specified by providing a discrete scenario set, containing possible realizations of the objective function coefficients. The concept of belief function in the traditional and possibilistic setting is applied to define a set of admissible probability distributions over the scenario set. The generalized Hurwicz criterion is then used to compute a solution. In this paper, the complexity of the resulting problem is explored. Some exact and approximation methods of solving it are proposed.

翻译：本文考虑目标函数系数存在不确定性的优化问题。不确定性通过提供包含目标函数系数可能实现值的离散情景集来定义。将传统及可能性框架下的信任函数概念应用于定义情景集上的一组可容许概率分布，进而采用广义Hurwicz准则求解。本文探讨了由此产生问题的计算复杂性，并提出了若干精确求解与近似求解方法。