Abstract
We consider the design of semidefinite programming (SDP) based approximation algorithm for the problem Max Hypergraph Cut with Limited Unbalance (MHC-LU): Find a partition of the vertices of a weighted hypergraph H = (V,E) into two subsets V 1, V 2 with ||V 2| − |V 1|| ⩽ u for some given u and maximizing the total weight of the edges meeting both V 1 and V 2. The problem MHC-LU generalizes several other combinatorial optimization problems including Max Cut, Max Cut with Limited Unbalance (MC-LU), Max Set Splitting, Max Ek-Set Splitting and Max Hypergraph Bisection. By generalizing several earlier ideas, we present an SDP randomized approximation algorithm for MHC-LU with guaranteed worst-case performance ratios for various unbalance parameters τ = u/|V |. We also give the worst-case performance ratio of the SDP-algorithm for approximating MHC-LU regardless of the value of τ. Our strengthened SDP relaxation and rounding method improve a result of Ageev and Sviridenko (2000) on Max Hypergraph Bisection (MHC-LU with u = 0), and results of Andersson and Engebretsen (1999), Gaur and Krishnamurti (2001) and Zhang et al. (2004) on Max Set Splitting (MHC-LU with u = |V|). Furthermore, our new formula for the performance ratio by a tighter analysis compared with that in Galbiati and Maffioli (2007) is responsible for the improvement of a result of Galbiati and Maffioli (2007) on MC-LU for some range of τ.
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Xu, B., Yu, X., Zhang, X. et al. An SDP randomized approximation algorithm for max hypergraph cut with limited unbalance. Sci. China Math. 57, 2437–2462 (2014). https://doi.org/10.1007/s11425-014-4900-5
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DOI: https://doi.org/10.1007/s11425-014-4900-5
Keywords
- max hypergraph cut with limited unbalance
- approximation algorithm
- performance ratio
- semidefinite programming relaxation