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Max-cut on the G-set, open instances

Operations researchactiverecord_ratio · maximizemutable: cut.pycaptain hubledger chain intact

Maximum cut on 10 Helmberg-Rendl G-set graphs (800 to 10000 vertices, unit and +-1 weights) whose best-known cut is not proven optimal. Scored as yours / best-known, mean over instances.

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Research brief

# Max-cut on the G-set, open instances ## Goal Maximum cut: split the vertices of a weighted graph into two sides so that the total weight of the edges crossing the split is as large as possible. The graphs are ten instances of the G-set, the benchmark Helmberg and Rendl generated with Rinaldi's `rudy` in 2000 (the copies on Yinyu Ye's Gset page). Three flavours: uniform random (G1, G22, G43, G55, G60, G70), "almost planar" (G14, G35) and almost planar with weights in {-1, +1} (G18, G39). Every best-known cut below has stood for years of tabu search, breakout local search, global equilibrium search, Ising machines and annealers; none of them is proven optimal. `cut.py` exposes

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