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Given a graph G, a properk-coloring of G is a partition c = (S i) i ∈ [ 1 , k ] of V(G) into k stable sets S 1 , ... , S k . Given a weight function w : V (G) → R + , the weight of a color S i is defined as w (i) = max v ∈ S i w (v) and the weight of a coloringc as w (c) = ∑ i = 1 k w (i) . Guan and Zhu (Inf Process Lett 61(2):77–81, 1997) defined the weighted chromatic number of a pair (G, w), denoted by σ (G , w) , as the minimum weight of a proper coloring of G. The problem of determining σ (G , w) has received considerable attention during the last years, and has been proved to be notoriously hard: for instance, it is NP-hard on split graphs, unsolvable on n-vertex trees in time n o (log n) unless the ETH fails, and W[1]-hard on forests parameterized by the size of a largest tree. We focus on the so-called dual parameterization of the problem: given a vertex-weighted graph (G, w) and an integer k, is σ (G , w) ≤ ∑ v ∈ V (G) w (v) - k ? This parameterization has been recently considered by Escoffier (in: Proceedings of the 42nd international workshop on graph-theoretic concepts in computer science (WG). LNCS, vol 9941, pp 50–61, 2016), who provided an FPT algorithm running in time 2 O (k log k) · n O (1) , and asked which kernel size can be achieved for the problem. We provide an FPT algorithm in time 9 k · n O (1) , and prove that no algorithm in time 2 o (k) · n O (1) exists under the ETH. On the other hand, we present a kernel with at most (2 k - 1 + 1) (k - 1) vertices, and rule out the existence of polynomial kernels unless NP ⊆ coNP / poly , even on split graphs with only two different weights. Finally, we identify classes of graphs allowing for polynomial kernels, namely interval graphs, comparability graphs, and subclasses of circular-arc and split graphs, and in the latter case we present lower bounds on the degrees of the polynomials. [ABSTRACT FROM AUTHOR]

Given a graph G , a proper k-coloring of G is a partition c = ( S i ) i ∈ [ 0 , k − 1 ] of V ( G ) into k stable sets S 0 , … , S k − 1 . Given a weight function w : V ( G ) → R + , the weight of a color S i is defined as w ( i ) = max v ∈ S i ⁡ w ( v ) and the weight of a coloring c as w ( c ) = ∑ i = 0 k − 1 w ( i ) . Guan and Zhu (1997) [11] defined the weighted chromatic number of a pair ( G , w ) , denoted by σ ( G , w ) , as the minimum weight of a proper coloring of G . For a positive integer r , they also defined σ ( G , w ; r ) as the minimum of w ( c ) among all proper r -colorings c of G . The complexity of determining σ ( G , w ) when G is a tree was open for almost 20 years, until Araújo et al. (2014) [1] recently proved that the problem cannot be solved in time n o ( log ⁡ n ) on n -vertex trees unless the Exponential Time Hypothesis (ETH) fails. The objective of this article is to provide hardness results for computing σ ( G , w ) and σ ( G , w ; r ) when G is a tree or a forest, relying on complexity assumptions weaker than the ETH. Namely, we study the problem from the viewpoint of parameterized complexity, and we assume the weaker hypothesis FPT ≠ W [ 1 ] . Building on the techniques of Araújo et al., we prove that when G is a forest, the decision problem of computing σ ( G , w ) is W [1]-hard parameterized by the size of a largest connected component of G , and that computing σ ( G , w ; r ) is W [2]-hard parameterized by r . Our results rule out the existence of FPT algorithms for computing these invariants on trees or forests for many natural choices of the parameter. [ABSTRACT FROM AUTHOR]

A proper k-coloring of a graph G is a partition c = ( S i ) i ∈ [ 1 , k ] of V ( G ) into k stable sets S 1 , … , S k . Given a weight function w : V ( G ) → R + , the weight of a color S i is defined as w ( i ) = max v ∈ S i ⁡ w ( v ) and the weight of a coloring c as w ( c ) = ∑ i = 1 k w ( i ) . Guan and Zhu [Inf. Process. Lett., 1997] defined the weighted chromatic number of a pair ( G , w ), denoted by σ ( G , w ) , as the minimum weight of a proper coloring of G . For a positive integer r , they also defined σ ( G , w ; r ) as the minimum of w ( c ) among all proper r -colorings c of G . The complexity of determining σ ( G , w ) when G is a tree was open for almost 20 years, until Araújo et al. [SIAM J. Discrete Math., 2014] recently proved that the problem cannot be solved in time n o ( log ⁡ n ) on n -vertex trees unless the Exponential Time Hypothesis (ETH) fails. The objective of this article is to provide hardness results for computing σ ( G , w ) and σ ( G , w ; r ) when G is a tree or a forest, relying on complexity assumptions weaker than the ETH. Namely, we study the problem from the viewpoint of parameterized complexity, and we assume the weaker hypothesis FPT ≠ W [ 1 ] . Building on the techniques of Araújo et al. , we prove that when G is a forest, computing σ ( G , w ) is W [ 1 ] -hard parameterized by the size of a largest connected component of G , and that computing σ ( G , w ; r ) is W [ 2 ] -hard parameterized by r . Our results rule out the existence of FPT algorithms for computing these invariants on trees or forests for many natural choices of the parameter. [ABSTRACT FROM AUTHOR]