Approximation algorithms and hardness results for the clique packing problem

For a fixed family F of graphs, an F-packing in a graph G is a set of pairwise vertex-disjoint subgraphs of G, each isomorphic to an element of F. Finding an F-packing that maximizes the number of covered edges is a natural generalization of the maximum matching problem, which is just F={K₂}. In this paper we provide new approximation algorithms and hardness results for the K_r-packing problem where K_r={K₂,K₃,…,K_r}.We show that already for r=3 the K_r-packing problem is APX-complete, and, in fact, we show that it remains so even for graphs with maximum degree 4. On the positive side, we give an approximation algorithm with approximation ratio at most 2 for every fixed r. For r=3,4,5 we obtain better approximations. For r=3 we obtain a simple3/2-approximation, achieving a known ratio that follows from a more involved algorithm of Halldórsson. For r=4, we obtain a (3/2+?)-approximation, and for r=5 we obtain a (25/14+?)-approximation.     

An approximation algorithm for the traveling tournament problem

This paper describes the traveling tournament problem, a well-known benchmark problem in the field of tournament timetabling. We propose a new lower bound for the traveling tournament problem, and construct a randomized approximation algorithm yielding a feasible solution whose approximation ratio is less than 2+(9/4)/(n−1), where n is the number of teams. Additionally, we propose a deterministic approximation algorithm with the same approximation ratio using a derandomization technique. For the traveling tournament problem, the proposed algorithms are the first approximation algorithms with a constant approximation ratio, which is less than 2+3/4.     

Multi-criteria TSP: Min and max combined

We present randomized approximation algorithms for multi-criteria traveling salesman problems (TSP), where some objective functions should be minimized while others should be maximized. For the symmetric multi-criteria TSP (STSP), we present an algorithm that computes (2/3,3+ε)-approximate Pareto curves. Here, the first parameter is the approximation ratio for the objectives that should be maximized, and the second parameter is the ratio for the objectives that should be minimized. For the asymmetric multi-criteria TSP (ATSP), we obtain an approximation performance of (1/2,log₂n+ε).     

An iterative rounding 2-approximation algorithm for the k-partial vertex cover problem

We study a generalization of the vertex cover problem. For a given graph with weights on the vertices and an integer k, we aim to find a subset of the vertices with minimum total weight, so that at least k edges in the graph are covered. The problem is called the k-partial vertex cover problem. There are some 2-approximation algorithms for the problem. In the paper we do not improve on the approximation ratios of the previous algorithms, but we derive an iterative rounding algorithm. We present our technique in two algorithms. The first is an iterative rounding algorithm and gives a （2 ＋ Q/OPT ）-approximation for the k-partial vertex cover problem where Q is the largest finite weight in the problem definition and OPT is the optimal value for the instance. The second algorithm uses the first as a subroutine and achieves an approximation ratio of 2.     

The traveling salesman problem on cubic and subcubic graphs

We study the traveling salesman problem (TSP) on the metric completion of cubic and subcubic graphs, which is known to be NP-hard. The problem is of interest because of its relation to the famous 4/3-conjecture for metric TSP, which says that the integrality gap, i.e., the worst case ratio between the optimal value of a TSP instance and that of its linear programming relaxation (the subtour elimination relaxation), is 4/3. We present the first algorithm for cubic graphs with approximation ratio 4/3. The proof uses polyhedral techniques in a surprising way, which is of independent interest. In fact we prove constructively that for any cubic graph on $n$ vertices a tour of length $4n/3-2$ exists, which also implies the 4/3-conjecture, as an upper bound, for this class of graph-TSP. Recently, Mömke and Svensson presented an algorithm that gives a 1.461-approximation for graph-TSP on general graphs and as a side result a 4/3-approximation algorithm for this problem on subcubic graphs, also settling the 4/3-conjecture for this class of graph-TSP. The algorithm by Mömke and Svensson is initially randomized but the authors remark that derandomization is trivial. We will present a different way to derandomize their algorithm which leads to a faster running time. All of the latter also works for multigraphs.     

Independent sets in bounded-degree hypergraphs

In this paper we analyze several approaches to the Maximum Independent Set (MIS) problem in hypergraphs with degree bounded by a parameter Δ. Since independent sets in hypergraphs can be strong and weak, we denote by MIS (MSIS) the problem of finding a maximum weak (strong) independent set in hypergraphs, respectively. We propose a general technique that reduces the worst case analysis of certain algorithms on hypergraphs to their analysis on ordinary graphs. This technique allows us to show that the greedy algorithm for MIS that corresponds to the classical greedy set cover algorithm has a performance ratio of (Δ+1)/2. It also allows us to apply results on local search algorithms on graphs to obtain a (Δ+1)/2 approximation for the weighted MIS and (Δ+3)/5−? approximation for the unweighted case. We improve the bound in the weighted case to ⌈(Δ+1)/3⌉ using a simple partitioning algorithm. We also consider another natural greedy algorithm for MIS that adds vertices of minimum degree and achieves only a ratio of Δ−1, significantly worse than on ordinary graphs. For MSIS, we give two variations of the basic greedy algorithm and describe a family of hypergraphs where both algorithms approach the bound of Δ.     

Approximating the maximum 3-edge-colorable subgraph problem

We offer the following structural result: every triangle-free graph G of maximum degree 3 has 3 matchings which collectively cover at least of its edges, where γ_o(G) denotes the odd girth of G. In particular, every triangle-free graph G of maximum degree 3 has 3 matchings which cover at least 13/15 of its edges. The Petersen graph, where we can 3-edge-color at most 13 of its 15 edges, shows this to be tight. We can also cover at least 6/7 of the edges of any simple graph of maximum degree 3 by means of 3 matchings; again a tight bound.For a fixed value of a parameter k≥1, the Maximum k-Edge-Colorable Subgraph Problem asks to k-edge-color the most of the edges of a simple graph received in input. The problem is known to be APX-hard for all k≥2. However, approximation algorithms with approximation ratios tending to 1 as k goes to infinity are also known. At present, the best known performance ratios for the cases k=2 and k=3 were 5/6 and 4/5, respectively. Since the proofs of our structural result are algorithmic, we obtain an improved approximation algorithm for the case k=3, achieving approximation ratio of 6/7. Better bounds, and allowing also for parallel edges, are obtained for graphs of higher odd girth (e.g., a bound of 13/15 when the input multigraph is restricted to be triangle-free, and of 19/21 when C₅’s are also banned).     

Approximation algorithms for art gallery problems in polygons

In this paper, we present approximation algorithms for minimum vertex and edge guard problems for polygons with or without holes with a total of n vertices. For simple polygons, approximation algorithms for both problems run in O(n⁴) time and yield solutions that can be at most O(logn) times the optimal solution. For polygons with holes, approximation algorithms for both problems give the same approximation ratio of O(logn), but the running time of the algorithms increases by a factor of n to O(n⁵).     

Approximation results for a min-max location-routing problem

This paper studies a min-max location-routing problem, which aims to determine both the home depots and the tours for a set of vehicles to service all the customers in a given weighted graph, so that the maximum working time of the vehicles is minimized. The min-max objective is motivated by the needs of balancing or fairness in vehicle routing applications. We have proved that unless NP=P, it is impossible for the problem to have an approximation algorithm that achieves an approximation ratio of less than 4/3. Thus, we have developed the first constant ratio approximation algorithm for the problem. Moreover, we have developed new approximation algorithms for several variants, which improve the existing best approximation ratios in the previous literature.     

The M-band cardinal orthogonal scaling function

The M-band symmetric cardinal orthogonal scaling function with compact support is of interest in several applications such as sampling theory, signal processing, computer graphics, and numerical algorithms. In this paper, we provide a complete mathematical analysis for the M-band symmetric cardinal orthogonal scaling function. Firstly, we generalize some results of the cardinal orthogonal scaling function from the special case M=2 to the most general case M?2. Also, we find some new results. Secondly, we obtain the characterizations of the M-band symmetric cardinal orthogonal scaling function and revisit some known examples to prove our theory.     

Approximation for Minimum Triangulations of Simplicial Convex 3-Polytopes

A minimum triangulation of a convex 3-polytope is a triangulation that contains the minimum number of tetrahedra over all its possible triangulations. Since finding minimum triangulations of convex 3-polytopes was recently shown to be NP-hard, it becomes significant to find algorithms that give good approximation. In this paper we give a new triangulation algorithm with an improved approximation ratio 2 - Ω(1/\sqrt n ) , where n is the number of vertices of the polytope. We further show that this is the best possible for algorithms that only consider the combinatorial structure of the polytopes. Received August 5, 2000, and in revised form March 29, 2001, and May 3, 2001. Online publication October 12, 2001.     

Approximability results for the resource-constrained project scheduling problem with a single type of resources

In this paper, we consider the well-known resource-constrained project scheduling problem. We give some arguments that already a special case of this problem with a single type of resources is not approximable in polynomial time with an approximation ratio bounded by a constant. We prove that there exist instances for which the optimal makespan values for the non-preemptive and the preemptive problems have a ratio of O(logn), where n is the number of jobs. This means that there exist instances for which the lower bound of Mingozzi et al. has a bad relative error of O(logn), and the calculation of this bound is an NP-hard problem. In addition, we give a proof that there exists a type of instances for which known approximation algorithms with polynomial time complexity have an approximation ratio of at least equal to $O(\sqrt{n})$ , and known lower bounds have a relative error of at least equal to O(logn). This type of instances corresponds to the single machine parallel-batch scheduling problem 1|p?batch,b=∞|C _max.     

On finding a large number of 3D points with a small diameter

Given a set S of n points in R³, we wish to decide whether S has a subset of size at least k with Euclidean diameter at most r. It is unknown whether this decision problem is NP-hard. The two closely related optimization problems, (i) finding a largest subset of diameter at most r, and (ii) finding a subset of the smallest diameter of size at least k, were recently considered by Afshani and Chan. For maximizing the size, they presented several polynomial-time algorithms with constant approximation factors, the best of which has a factor of . For maximizing the diameter, they presented a polynomial-time approximation scheme. In this paper, we present improved approximation algorithms for both optimization problems. For maximizing the size, we present two algorithms: the first one improves the approximation factor to 2.5 and the running time by an O(n) factor; the second one improves the approximation factor to 2 and the running time by an O(n²) factor. For minimizing the diameter, we improve the running time of the PTAS from O(nlogn+2^O(1/ε3)n) to O(nlogn+2^{O(1/(ε1.5logε))}n).     

Relay placement for fault tolerance in wireless networks in higher dimensions

In this paper we consider the problem of adding the smallest number of additional (relay) nodes to a network of static nodes with limited communication range so that the induced communication graph is 2-connected (we consider both edge and vertex connectivity). The problem is NP-hard. We develop algorithms that find close to optimal solutions for both edge and vertex connectivity. We prove the algorithms have an approximation ratio of 2M for nodes distributed in a d-dimensional Euclidean space, where M is the maximum node degree of a Minimum Spanning Tree in d dimensions using Euclidean metrics. In addition, our methods extend with the same approximation guarantees to a generalization when the locations of relays are required to avoid certain polygonal regions (obstacles).     

Quasi topologies and rational approximation

We obtain a characterization for L_p approximation by analytic functions on compact plane sets which is analogous to Vitushkin's characterization for uniform approximation. For p = 2 this was done by Havin by use of Cartan's fine topology; we study the general case by use of quasi topologies.     

Approximating the maximum 2- and 3-edge-colorable subgraph problems

For a fixed value of a parameter k≥2, the Maximum k-Edge-Colorable Subgraph Problem consists in finding k edge-disjoint matchings in a simple graph, with the goal of maximising the total number of edges used. The problem is known to be -hard for all k, but there exist polynomial time approximation algorithms with approximation ratios tending to 1 as k tends to infinity. Herein we propose improved approximation algorithms for the cases of k=2 and k=3, having approximation ratios of 5/6 and 4/5, respectively.     

Refining Cosmetatos' Approximation for the Mean Waiting Time in the M/D/s Queue

This paper deals with refining Cosmetatos's approximation for the mean waiting time in an M/D/s queue. Although his approximation performs quite well in heavy traffic, it overestimates the true value when the number of servers is large or the traffic is light. We first focus on a normalized quantity that is a ratio of the mean waiting times for the M/D/s and M/M/s queues. Using some asymptotic properties of the quantity, we modify Cosmetatos's approximation to obtain better accuracy both for large s and in light traffic. To see the quality of our approximation, we compare it with the exact value and some previous approximations. Extensive numerical tests indicate that the relative percentage error is less than 1% for almost all cases with s ≤ 20 and at most 5% for other cases.     

A new coupled approach high accuracy numerical method for the solution of 3D non-linear biharmonic equations

In this paper, we derive a new fourth order finite difference approximation based on arithmetic average discretization for the solution of three-dimensional non-linear biharmonic partial differential equations on a 19-point compact stencil using coupled approach. The numerical solutions of unknown variable u(x,y,z) and its Laplacian ∇²u are obtained at each internal grid point. The resulting stencil algorithm is presented which can be used to solve many physical problems. The proposed method allows us to use the Dirichlet boundary conditions directly and there is no need to discretize the derivative boundary conditions near the boundary. We also show that special treatment is required to handle the boundary conditions. The new method is tested on three problems and the results are compared with the corresponding second order approximation, which we also discuss using coupled approach.     

When a worse approximation factor gives better performance: a 3-approximation algorithm for the vertex k-center problem

The vertex k-center selection problem is a well known NP-Hard minimization problem that can not be solved in polynomial time within a \(\rho < 2\) approximation factor, unless \(P=NP\). Even though there are algorithms that achieve this 2-approximation bound, they perform poorly on most benchmarks compared to some heuristic algorithms. This seems to happen because the 2-approximation algorithms take, at every step, very conservative decisions in order to keep the approximation guarantee. In this paper we propose an algorithm that exploits the same structural properties of the problem that the 2-approximation algorithms use, but in a more relaxed manner. Instead of taking the decision that guarantees a 2-approximation, our algorithm takes the best decision near the one that guarantees the 2-approximation. This results in an algorithm with a worse approximation factor (a 3-approximation), but that outperforms all the previously known approximation algorithms on the most well known benchmarks for the problem, namely, the pmed instances from OR-Lib (Beasly in J Oper Res Soc 41(11):1069–1072, 1990) and some instances from TSP-Lib (Reinelt in ORSA J Comput 3:376–384, 1991). However, the \(O(n^4)\) running time of this algorithm becomes unpractical as the input grows. In order to improve its running time, we modified this algorithm obtaining a \(O(n^2 \log n)\) heuristic that outperforms not only all the previously known approximation algorithms, but all the polynomial heuristics proposed up to date.     

The dual eigenvalue problems for p-Laplacian

We consider the eigenvalue gap/ratio of the p-Laplacian eigenvalue problems, and obtain the minimizer of the eigenvalue gap for the single-well potential function. For the dual result, we also obtain the minimizer of the eigenvalue ratio for the single-barrier density function for p-Laplacian. This extends the results of the classical problem for the case p=2.