Approximation Algorithms for \(\alpha\)-bisubmodular Function Maximization Subject to Matroid Constraint

Wenqi Wang *

School of Mathematical Science and Institute of Mathematics, Nanjing Normal University, Nanjing, China.

*Author to whom correspondence should be addressed.


Abstract

We design an approximation algorithm for maximizing \(\alpha\)-bisubmodular function with matroid constraint, where the \(\alpha\)-bisubmodular function is a generalization of a bisubmodular function. The concept of \(\alpha\)- bisubmodularity is provided by Huber, Krokhin, and Powell [[1], 2014], rank function of delta-matroids and the cut capacity of directed networks have \(\alpha\)-bisubmodularity. We consider the two cases of the problem, monotone and non-monotone objective function, respectively. We also show that the running time is
polynomial.

Keywords: \(\alpha\)-bisubmodular function, combinatorial optimization, greedy algorithm, matroid constraint


How to Cite

Wang, Wenqi. 2023. “Approximation Algorithms for \(\alpha\)-Bisubmodular Function Maximization Subject to Matroid Constraint”. Journal of Advances in Mathematics and Computer Science 38 (3):42-48. https://doi.org/10.9734/jamcs/2023/v38i31750.

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