Pointwise efficiency in multiobjective stochastic linear programming

In most of the approaches to the Multiobjective Stochastic Linear Programming problem that have been proposed in the literature, the notion of quality of a solution is not adequately defined. This paper reconsiders this problem from a decision point of view, in contexts where either the decision maker’s preference structure cannot be described by a utility function, or where this structure is expressed by an unknown non-decreasing utility function and the probability distribution of the random parameters is unknown. The paper defines a fundamental set of ‘pointwise admissible’ solutions, as well as several subsets of particular interest. It discusses the relevance of these various pointwise efficient sets, their interrelations, and their practical identification.