Abstract
A new objective for the Weber location problem is proposed. The weights of the Weber problem are drawn form a multivariate distribution. The objective is to minimize the probability of over-running a cost threshold. Alternatively, we may wish to minimize the threshold for a given probability. These concepts can be applied to many optimization models as well. We analyze the problem and develop an optimal algorithm to solve it. An illustrative example is solved and computational results for randomly generated problems are presented.
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