A polyhedral study of the acyclic coloring problem

Acyclic and k-distance coloring of the grid

The concept of acyclic coloring was introduced by Grünbaum [5] and is a generalization of point arboricity.A proper k-coloring of the vertices of a graph Gis said to be acyclic if G contains no two-colored cycle. The acyclic chromatic number of a graph G, denoted by a(G), is the minimum value of k for which G has an acyclic k-coloring. Let a(n) denote the maximum value of the acyclic chromatic number among all graphs of genus n. In [5], Grünbaum conjectured that a(0) = 5 and proved that a(0)≤9. The conjecture was proved by Borodin [3] after the upper bound was improved three times in [7], [1] and [6]. In [2], we proved that a(1)≤a(0) + 3. The purpose of this paper is to prove the followingTheorem. Any graph of genus n>0 can be acyclically colored with 4n + 4 colors.It is not known for any n>0 whether a(n)>H(n), the Heawood number [8].

An acyclic coloring of a graph G is a proper vertex coloring ( no two adjacent vertices of G have the same color) such that the induced sub graph of any two color classes is acyclic. The minimum number of colors required for acyclic coloring of a graph G is called as its acyclic chromatic number and is denoted by a(G). In this paper, we present the structure and coloring algorithm of central graph of Gear Graph Gn and we obtain the exact value of its acyclic chromatic number.

The Chinese postman problem with time-dependent travel time (CPPTDT) is a generalization of the classical Chinese postman problem (CPP), where the travel time on an arc depends on the time of beginning of travel along it. While CPP and its almost static variants can be solved by integer program successfully, there are very challenging time varying CPP variants, such as CPPTDT, which are difficult to be formulated directly. The first and the only integer programming formulation modeling the time varying CPP directly was presented in the pioneering work of Wang and Wen (Comput Math Appl 44:375---387, 2002), which was unfortunately based on a strong assumption that each basic cycle in the graph must visit the depot. In this work, we propose a new integer programming formulation for the CPPTDT without any unrealistic assumptions, namely, the arc-cycle formulation, which can be viewed as an extended version of the formulation given by Wang and Wen. The constraint set of this formulation can be divided into two parts. The first part has a strong combinatorial structure, which is linear and used to define the polytope of cycle-path alternation sequence (CPAS). We determine the dimension of the CPAS polytope and identify the facet defining inequalities which may be helpful to tighten the integer programming formulation. The second part is closely related to time-dependent travel time and is nonlinear. The linearization is provided to the case when all the travel times are piecewise functions of beginning time, and several strong, valid inequalities are also proposed. The computation results with a cutting plane algorithm using the new cuts are reported on several randomly generated instances.

We describe a procedure for determining a few of the largest singular values of a large sparse matrix. The method by Golub and Kent which uses the method of modified moments for estimating the eigenvalues of operators used in iterative methods for the solution of linear systems of equations is appropriately modified in order to generate a sequence of bidiagonal matrices whose singular values approximate those of the original sparse matrix. A simple Lanczos recursion is proposed for determining the corresponding left and right singular vectors. The potential asynchronous computation of the bidiagonal matrices using modified moments with the iterations of an adapted Chebyshev semi-iterative (CSI) method is an attractive feature for parallel computers. Comparisons in efficiency and accuracy with an appropriate Lanczos algorithm (with selective re-orthogonalization) are presented on large sparse (rectangular) matrices arising from applications such as information retrieval and seismic reflection tomography. This procedure is essentially motivated by the theory of moments and Gauss quadrature.

Given an initial marking and final marking for a Petri net model, an optimal firing sequence problem is defined as the problem to find an optimal transition firing sequence to minimize the objective function. For the purpose of analysis of general integer programming problems, we propose a Petri net representation and reachability analysis of integer programming problems. In the proposed method, an integer programming problem is converted into the optimal firing sequence problem of Petri nets. By utilizing the proposed algorithm, integer programming problems can be visualized and analyzed by the Petri net theory. We apply the proposed methodology to the scheduling problems of dual armed cluster tools. The valid inequalities are derived from the reachability analysis. Numerical results show that those valid inequalities can significantly reduce the computational time of the original integer programming problem.

The Football Pool Polytope

The rainbow connection was first introduced by Chartrand in 2006 and then in 2009 Krivelevich and Yuster first time introduced the rainbow vertex connection. Let graph be a connected graph. The rainbow vertex-connection is the assignment of color to the vertices of a graph , if every vertex on the graph is connected by a path graph that has interior vertices in different colors. The minimum number of colors from the rainbow vertex coloring in the graph is called rainbow vertex connection number which is denoted . The results of the research are the rainbow vertex connection number of bull graph, net graph, triangular ladder graph, and graph composition (Pn[P1]).

Computer Solution of Large Linear Systems

Optimal sequencing of tasks in an aluminium smelter casthouse

Forming minimum-cost machine cells with exceptional parts using zero-one integer programming

Large sparse symmetric indefinite matrices are notoriously hard to precondition. They often lack diagonal dominance and exhibit Schur-complements that render zero fill-in preconditioning ineffective. Pivoting, a necessity for stable LDLt factorizations, complicates parallel approaches that can take advantage of the latest massively-parallel HPC hardware such as GPUs. We present an approach based on ad-hoc blocking and reordering strategies that allows local, independent collective-oriented processing of small dense blocks. A hybrid block-memory layout compensates for irregular memory access patterns found in sparse matrices. Our method allows restricted fill-in, supernodal pivoting and a dual threshold dropping strategy at little additional cost. It delivers robust preconditioners that in our experiments obtain an average speedup of ~6x even for tough matrices from optimization problems.

For accelerating the convergence of numerical computation of sparse matrices, the classical approach is to partition sparse matrices into block-diagonal structures by graph partitioning algorithms, and then apply distinct preconditioning strategies for different blocks, which enable parallel processing of individual blocks and significantly enhances the efficiency. This paper comprehensively analyzes typical graph partitioning algorithms, including METIS, ParMETIS, hMETIS and Scotch in terms of efficiency and resource consumption. By experiments on standardized test cases, we systematically compare these algorithms and summarizes their respective characteristics and optimal application scenarios for future work.

High blood pressure or hypertension is a global public health issue. High blood pressure can lead to cardiovascular disease, stroke, diabetes and others. The diet problem of high blood pressure patients has always been concerned by the field of operational research. Some previous and recent research have proposed that diet plays an important role in affecting the condition of high blood pressure. A balanced diet will provide essential nutrients for high blood pressure patients that help to control and lower blood pressure. The purpose of this study is to construct a diet menu that meet the nutritional requirements of high blood pressure patient as well as minimize the food cost by developing a mathematical model using linear and integer programming approaches. The model of this study involved 10 type of food groups with 413 types of food variables based on the Malaysian recipes. The findings show that integer programming is a good alternative for linear programming. Integer programming leads to an optimal and effective solutions for the diet problem of high blood pressure patients.

An integer programming approach to scheduling the transshipment of products at cross-docks in less-than-truckload industries