Asymptotically Optimal Weighted Edge Colorings via Local Bin Packing
arXiv:2611.03190
Abstract
We study weighted edge coloring, where each edge of a graph has a weight in , and colors are assigned so that the incident weight of each color at every vertex is at most one. The objective is to minimize the number of colors, denoted by . This generalizes classical edge coloring (all weights are one) and bin packing ( is a star). Two natural lower bounds are the maximum weighted degree and the maximum local bin-packing number : the maximum, over vertices, of the minimum number of unit bins needed to pack the incident weights. We have . How closely these local lower bounds approximate the global optimum is a longstanding open problem. Our main result establishes an asymptotic weighted analogue of Vizing's theorem: every simple graph admits a coloring using at most colors. Thus local bin packings can be made globally consistent with asymptotically vanishing relative loss, even in nonbipartite graphs. Our local-to-global rounding framework coordinates feasible local packing distributions into a partial coloring, leaving only uncolored weight at every vertex. For bipartite multigraphs, we prove , establishing the Chung--Ross conjecture [SICOMP'91] asymptotically. For loopless multigraphs, we obtain the exact bound . Both leading coefficients are optimal, giving weighted analogues of the classical Kőnig--Shannon bounds. Further upper and lower bounds show that the classical factor- separation does not persist with the local bin-packing benchmark. We also disprove the exact weighted-degree conjecture of Feige and Singh [ESA'08]. Our upper bounds have polynomial-time algorithms, and their existence statements are formalized in Lean 4.
arXiv comment94 pages