Posimodular function optimization

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Abstract

A function f : 2V → IR on a finite set V is posimodular if f(X) + f(Y) ≥ f(X\Y) + f(Y\X), for all X, Y ⊆ V. Posimodular functions often arise in combinatorial optimization such as undirected cut functions. We consider the problem of finding a nonempty subset X minimizing f(X), when the posimodular function f is given by oracle access. We show that posimodular function minimization requires exponential time, contrasting with the polynomial solvability of submodular function minimization that forms another generalization of cut functions. On the other hand, the problem is fixed-parameter tractable in terms of the size of the image (or range) of f. In more detail, we show that Ω(20.3219nTf) time is necessary and O(20.92nTf) sufficient, where Tf denotes the time for one function evaluation. When the image of f is D = {0, 1,...,d}, O(21.271dnTf) time is sufficient and Ω(20.1609dTf) necessary. We can also generate all sets minimizing f in time 2O(d) n2Tf . Finally, we also consider the problem of maximizing a given posimodular function, showing that it requires at least 2n−1Tf time in general, while it has time complexity Θ(nd−1Tf) when D = {0, 1,...,d} is the image of f, for integer d.

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APA

Halldórsson, M. M., Ishii, T., Makino, K., & Takazawa, K. (2017). Posimodular function optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10389 LNCS, pp. 437–448). Springer Verlag. https://doi.org/10.1007/978-3-319-62127-2_37

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