This paper considers an optimal location problem, called stochastic weighted Weber problem. It is formulated to a stochastic programming problem, and common approach for solving is to utilize the following four criteria: expectation of its objective function value, its variance, achievement probability for a given goal value by the decision-maker, and its fractile. It can be reformulated to a deterministic programming problem, if the locater can give her/his criterion in the above criteria or their highbred type. However, it is often hard to decide her/his criterion. This paper proposes to consider all the four criteria simultaneously. Then, it can be reformulated to four-objective deterministic programming problem, whose objective functions are corresponded to the above four criteria. Since multiobjective programming problems generally have too many Pareto optimal solution, this paper proposes an interactive solution approach for finding a satisficing location for her/him among the set of Pareto optimal solutions. © Springer-Verlag Berlin Heidelberg 2013.