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SUBMODULAR MAXIMIZATION OF CONCAVE UTILITY FUNCTIONS COMPOSED WITH A SET-UNION OPERATOR WITH APPLICATIONS TO MAXIMAL COVERING LOCATION PROBLEMS

[ARTICLE] This paper studies discrete optimization problems that maximize the expected value of a concave, strictly increasing function composed with a set-union operator, modeling a decision maker's utility function.

by Ivana LJUBIC (ESSEC Business School),  Stefano CONIGLIO, Fabio FURINI

We study a family of discrete optimization problems asking for the maximization of the expected value of a concave, strictly increasing, and differentiable function composed with a set-union operator. The expected value is computed with respect to a set of coefficients taking values from a discrete set of scenarios. The function models the utility function of the decision maker, while the set-union operator models a covering relationship between two ground sets, a set of items and a set of metaitems. This problem generalizes the problem introduced by Ahmed S, Atamtürk A (Mathematical programming 128(1-2):149–169, 2011), and it can be modeled as a mixed integer nonlinear program involving binary decision variables associated with the items and metaitems. Its goal is to find a subset of metaitems that maximizes the total utility corresponding to the items it covers.

[Please read the research paper here]

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