A graph coloring heuristic using partial solutions and a reactive tabu scheme

Most of the recent heuristics for the graph coloring problem start from an infeasible k-coloring (adjacent vertices may have the same color) and try to make the solution feasible through a sequence of color exchanges. In contrast, our approach (called FOO-PARTIALCOL), which is based on tabu search, considers feasible but partial solutions and tries to increase the size of the current partial solution. A solution consists of k disjoint stable sets (and, therefore, is a feasible, partial k-coloring) and a set of uncolored vertices. We introduce a reactive tabu tenure which substantially enhances the performance of both our heuristic as well as the classical tabu algorithm (called TABUCOL) proposed by Hertz and de Werra [Using tabu search techniques for graph coloring, Computing 1987;39:345–51]. We will report numerical results on different benchmark graphs and we will observe that FOO-PARTIALCOL, though very simple, outperforms TABUCOL on some instances, provides very competitive results on a set of benchmark graphs which are known to be difficult, and outperforms the best-known methods on the graph flat300_28_0. For this graph, FOO-PARTIALCOL finds an optimal coloring with 28 colors. The best coloring achieved to date uses 31 colors. Algorithms very close to TABUCOL are still used as intensification procedures in the best coloring methods, which are evolutionary heuristics. FOO-PARTIALCOL could then be a powerful alternative. In conclusion FOO-PARTIALCOL is one of the most efficient simple local search coloring methods yet available.     

On the complexity of some colorful problems parameterized by treewidth

In this paper, we study the complexity of several coloring problems on graphs, parameterized by the treewidth of the graph.

1.

The List Coloring problem takes as input a graph G, together with an assignment to each vertex v of a set of colors C_v. The problem is to determine whether it is possible to choose a color for vertex v from the set of permitted colors C_v, for each vertex, so that the obtained coloring of G is proper. We show that this problem is W[1]-hard, parameterized by the treewidth of G. The closely related Precoloring Extension problem is also shown to be W[1]-hard, parameterized by treewidth.

2.

An equitable coloring of a graph G is a proper coloring of the vertices where the numbers of vertices having any two distinct colors differs by at most one. We show that the problem is hard for W[1], parameterized by the treewidth plus the number of colors. We also show that a list-based variation, List Equitable Coloring is W[1]-hard for forests, parameterized by the number of colors on the lists.

3.

The list chromatic numberχ_l(G) of a graph G is defined to be the smallest positive integer r, such that for every assignment to the vertices v of G, of a list L_v of colors, where each list has length at least r, there is a choice of one color from each vertex list L_v yielding a proper coloring of G. We show that the problem of determining whether χ_l(G)?r, the List Chromatic Number problem, is solvable in linear time on graphs of constant treewidth.

     

A note on 2-facial coloring of plane graphs

An l-facial coloring of a plane graph is a vertex coloring such that any two different vertices joined by a facial walk of length at most l receive distinct colors. It is known that every plane graph admits a 2-facial coloring using 8 colors [D. Král, T. Madaras, R. Škrekovski, Cyclic, diagonal and facial coloring, European J. Combin. 3-4 (26) (2005) 473-490]. We improve this bound for plane graphs with large girth and prove that if G is a plane graph with girth g?14 (resp. 10, 8) then G admits a 2-facial coloring using 5 colors (resp. 6, 7). Moreover, we give exact bounds for outerplanar graphs and K₄-minor free graphs.     

On the oriented chromatic number of grids

In this paper, we focus on the oriented coloring of graphs. Oriented coloring is a coloring of the vertices of an oriented graph G without symmetric arcs such that (i) no two neighbors in G are assigned the same color, and (ii) if two vertices u and v such that (u,v)∈A(G) are assigned colors c(u) and c(v), then for any (z,t)∈A(G), we cannot have simultaneously c(z)=c(v) and c(t)=c(u). The oriented chromatic number of an unoriented graph G is the smallest number k of colors for which any of the orientations of G can be colored with k colors.The main results we obtain in this paper are bounds on the oriented chromatic number of particular families of planar graphs, namely 2-dimensional grids, fat trees and fat fat trees.     

List edge multicoloring in graphs with few cycles

The list edge multicoloring problem is a version of edge coloring where every edge e has a list of available colors L(e) and an integer demand x(e). For each e, we have to select x(e) colors from L(e) such that adjacent edges receive disjoint sets of colors. Marcotte and Seymour proved a characterization theorem for list edge multicoloring trees, which can be turned into a polynomial time algorithm. We present a slightly more general algorithm that works also on odd cycles. A variant of the method leads to a randomized polynomial time algorithm for handling even cycles as well.     

On acyclic edge coloring of toroidal graphs

Let c be a proper edge coloring of a graph G. If there exists no bicolored cycle in G with respect to c, then c is called an acyclic edge coloring of G. Let G be a planar graph with maximum degree Δ and girth g. In Dong and Xu (2010) [8], Dong and Xu proved that G admits an acyclic edge coloring with Δ(G) colors if Δ?8 and g?7, or Δ?6 and g?8, or Δ?5 and g?9, or Δ?4 and g?10, or Δ?3 and g?14. In this note, we fix a small gap in the proof of Dong and Xu (2010) [8], and generalize the above results to toroidal graphs.     

Perfectly colorable graphs

We define a perfect coloring of a graph G as a proper coloring of G such that every connected induced subgraph H of G uses exactly ω(H) many colors where ω(H) is the clique number of H. A graph is perfectly colorable if it admits a perfect coloring. We show that the class of perfectly colorable graphs is exactly the class of perfect paw-free graphs. It follows that perfectly colorable graphs can be recognized and colored in linear time.     

Consensus models: Computational complexity aspects in modern approaches to the list coloring problem

In the paper we study new approaches to the problem of list coloring of graphs. In the problem we are given a simple graph G=(V,E) and, for every v∈V, a nonempty set of integers S(v); we ask if there is a coloring c of G such that c(v)∈S(v) for every v∈V. Modern approaches, connected with applications, change the question—we now ask if S can be changed, using only some elementary transformations, to ensure that there is such a coloring and, if the answer is yes, what is the minimal number of changes. In the paper for studying the adding, the trading and the exchange models of list coloring, we use the following transformations:

•

adding of colors (the adding model): select two vertices u, v and a color c∈S(u); add c to S(v), i.e. set S(v):=S(v)∪{c};

•

trading of colors (the trading model): select two vertices u, v and a color c∈S(u); move c from S(u) to S(v), i.e. set S(u):=S(u)?{c} and S(v):=S(v)∪{c};

•

exchange of colors (the exchange model): select two vertices u, v and two colors c∈S(u), d∈S(v); exchange c with d, i.e. set S(u):=(S(u)?{c})∪{d} and S(v):=(S(v)?{d})∪{c}.

Our study focuses on computational complexity of the above models and their edge versions. We consider these problems on complete graphs, graphs with bounded cyclicity and partial k-trees, receiving in all cases polynomial algorithms or proofs of NP-hardness.     

Algorithmic Aspects of Acyclic Edge Colorings

Abstract. A proper coloring of the edges of a graph G is called acyclic if there is no two-colored cycle in G . The acyclic edge chromatic number of G , denoted by a'(G) , is the least number of colors in an acyclic edge coloring of G . For certain graphs G , a'(G)\geq Δ(G)+2 where Δ(G) is the maximum degree in G . It is known that a'(G)≤ Δ + 2 for almost all Δ -regular graphs, including all Δ -regular graphs whose girth is at least cΔ log Δ . We prove that determining the acyclic edge chromatic number of an arbitrary graph is an NP-complete problem. For graphs G with sufficiently large girth in terms of Δ(G) , we present deterministic polynomial-time algorithms that color the edges of G acyclically using at most Δ(G)+2 colors.     

Adjacent vertex-distinguishing edge and total chromatic numbers of hypercubes

An adjacent vertex-distinguishing edge coloring of a simple graph G is a proper edge coloring of G such that incident edge sets of any two adjacent vertices are assigned different sets of colors. A total coloring of a graph G is a coloring of both the edges and the vertices. A total coloring is proper if no two adjacent or incident elements receive the same color. An adjacent vertex-distinguishing total coloring h of a simple graph G=(V,E) is a proper total coloring of G such that H(u)≠H(v) for any two adjacent vertices u and v, where H(u)={h(wu)|wu∈E(G)}∪{h(u)} and H(v)={h(xv)|xv∈E(G)}∪{h(v)}. The minimum number of colors required for an adjacent vertex-distinguishing edge coloring (resp. an adjacent vertex-distinguishing total coloring) of G is called the adjacent vertex-distinguishing edge chromatic number (resp. adjacent vertex-distinguishing total chromatic number) of G and denoted by (resp. χat(G)). In this paper, we consider the adjacent vertex-distinguishing edge chromatic number and adjacent vertex-distinguishing total chromatic number of the hypercube Qn, prove that for n?3 and χat(Qn)=Δ(Qn)+2 for n?2.     

Coloring inductive graphs on-line

In this paper we consider the problem of on-line graph coloring. In an instance of on-line graph coloring, the nodes are presented one at a time. As each node is presented, its edges to previously presented nodes are also given. Each node must be assigned a color, different from the colors of its neighbors, before the next node is given. LetA(G) be the number of colors used by algorithmA on a graphG and letx(G) be the chromatic number ofG. The performance ratio of an on-line graph coloring algorithm for a class of graphsC is max_{G C(A(G)/(G))}. We consider the class ofd-inductive graphs. A graphG isd-inductive if the nodes ofG can be numbered so that each node has at mostd edges to higher-numbered nodes. In particular, planar graphs are 5-inductive, and chordal graphs arex(G)-inductive. First Fit is the algorithm that assigns each node the lowest-numbered color possible. We show that ifG isd-inductive, then First Fit usesO(d logn) colors onG. This yields an upper bound ofo(logn) on the performance ratio of First Fit on chordal and planar graphs. First Fit does as well as any on-line algorithm ford-inductive graphs: we show that, for anyd and any on-line graph coloring algorithmA, there is ad-inductive graph that forcesA to use (d logn) colors to colorG. We also examine on-line graph coloring with lookahead. An algorithm is on-line with lookaheadl, if it must color nodei after examining only the firstl+i nodes. We show that, forl/logn, the lower bound ofd logn colors still holds.This research was supported by an IBM Graduate Fellowship.     

随机图的点可区别V-全染色算法

图[G]的点可区别V-全染色就是相邻的边、顶点与其关联边必须染不同的颜色,同时要求所有顶点的色集合也不相同,所用的最少颜色数称为图[G]的点可区别V-全色数。根据点可区别V-全染色的约束规则,设计了一种启发式的点可区别V-全染色算法,该算法借助染色矩阵及色补集合逐步迭代交换,每次迭代交换后判断目标函数值,当目标函数值满足要求时染色成功。给出了算法的详细描述、算法分析和算法测试结果,对给定点数的图进行了点可区别V-全染色猜想的验证。实验结果表明,该算法有很好的执行效率并可以得到给定图的点可区别V-全色数,并且算法的时间复杂度不超过[O(n3)]。     

Graphs with maximum degree 6 are acyclically 11-colorable

An acyclic k-coloring of a graph G is a proper vertex coloring of G, which uses at most k colors, such that the graph induced by the union of every two color classes is a forest. In this note, we prove that every graph with maximum degree six is acyclically 11-colorable, thus improving the main result of Yadav et al. (2009) [11].     

Bounded coloring of co-comparability graphs and the pickup and delivery tour combination problem

The Double Traveling Salesman Problem with Multiple Stacks is a vehicle routing problem in which pickups and deliveries must be performed in two independent networks. The items are stored in stacks and repacking is not allowed. Given a pickup and a delivery tour, the problem of checking if there exists a valid distribution of items into s stacks of size h that is consistent with the given tours, is known as Pickup and Delivery Tour Combination (PDTC) problem.In the paper, we show that the PDTC problem can be solved in polynomial time when the number of stacks s is fixed but the size of each stack is not. We build upon the equivalence between the PDTC problem and the bounded coloring (BC) problem on permutation graphs: for the latter problem, s is the number of colors and h is the number of vertices that can get a same color. We show that the BC problem can be solved in polynomial time when s is a fixed constant on co-comparability graphs, a superclass of permutation graphs. To the contrary, the BC problem is known to be hard on permutation graphs when h≥6 is a fixed constant, but s is unbounded.     

Algorithmic Aspects of Acyclic Edge Colorings

A proper coloring of the edges of a graph G is called acyclic if there is no two-colored cycle in G . The acyclic edge chromatic number of G , denoted by a'(G) , is the least number of colors in an acyclic edge coloring of G . For certain graphs G , a'(G)\geq Δ(G)+2 where Δ(G) is the maximum degree in G . It is known that a'(G)≤ Δ + 2 for almost all Δ -regular graphs, including all Δ -regular graphs whose girth is at least cΔ log Δ . We prove that determining the acyclic edge chromatic number of an arbitrary graph is an NP-complete problem. For graphs G with sufficiently large girth in terms of Δ(G) , we present deterministic polynomial-time algorithms that color the edges of G acyclically using at most Δ(G)+2 colors.     

A memetic algorithm for the Minimum Sum Coloring Problem

Given an undirected graph G, the Minimum Sum Coloring Problem (MSCP) is to find a legal assignment of colors (represented by natural numbers) to each vertex of G such that the total sum of the colors assigned to the vertices is minimized. This paper presents a memetic algorithm for MSCP based on a tabu search procedure with two neighborhoods and a multi-parent crossover operator. Experiments on a set of 77 well-known DIMACS and COLOR 2002–2004 benchmark instances show that the proposed algorithm achieves highly competitive results in comparison with five state-of-the-art algorithms. In particular, the proposed algorithm can improve the best known results for 15 instances.     

Weighted Coloring: further complexity and approximability results

Given a vertex-weighted graph G=(V,E;w), w(v)?0 for any v∈V, we consider a weighted version of the coloring problem which consists in finding a partition S=(S₁,…,Sk) of the vertex set of G into stable sets and minimizing where the weight of S is defined as . In this paper, we continue the investigation of the complexity and the approximability of this problem by answering some of the questions raised by Guan and Zhu [D.J. Guan, X. Zhu, A coloring problem for weighted graphs, Inform. Process. Lett. 61 (2) (1997) 77-81].     

On Coloring Unit Disk Graphs

In this paper the coloring problem for unit disk (UD) graphs is considered. UD graphs are the intersection graphs of equal-sized disks in the plane. Colorings of UD graphs arise in the study of channel assignment problems in broadcast networks. Improving on a result of Clark et al. [2] it is shown that the coloring problem for UD graphs remains NP-complete for any fixed number of colors k≥ 3 . Furthermore, a new 3-approximation algorithm for the problem is presented which is based on network flow and matching techniques. Received February 12, 1996; revised October 9, 1996.