On the complexity of the dualization problem

The computational complexity of discrete problems concerning the enumeration of solutions is addressed. The concept of an asymptotically efficient algorithm is introduced for the dualization problem, which is formulated as the problem of constructing irreducible coverings of a Boolean matrix. This concept imposes weaker constraints on the number of “redundant” algorithmic steps as compared with the previously introduced concept of an asymptotically optimal algorithm. When the number of rows in a Boolean matrix is no less than the number of columns (in which case asymptotically optimal algorithms for the problem fail to be constructed), algorithms based on the polynomialtime-delay enumeration of “compatible” sets of columns of the matrix is shown to be asymptotically efficient. A similar result is obtained for the problem of searching for maximal conjunctions of a monotone Boolean function defined by a conjunctive normal form.     

Computational complexity of the graph approximation problem

The computational complexity of the graph approximation problem is investigated. It is shown that the different variants of this problem are NP-hard both for undirected and directed graphs. A polynomial-time approximation scheme (PTAS) for one of the variants is presented.     

The computational complexity of the pooling problem

The pooling problem is an extension of the minimum cost flow problem defined on a directed graph with three layers of nodes, where quality constraints are introduced at each terminal node. Flow entering the network at the source nodes has a given quality, at the internal nodes (pools) the entering flow is blended, and then sent to the terminal nodes where all entering flow streams are blended again. The resulting flow quality at the terminals has to satisfy given bounds. The objective is to find a cost-minimizing flow assignment that satisfies network capacities and the terminals’ quality specifications. Recently, it was proved that the pooling problem is NP-hard, and that the hardness persists when the network has a unique pool. In contrast, instances with only one source or only one terminal can be formulated as compact linear programs, and thereby solved in polynomial time. In this work, it is proved that the pooling problem remains NP-hard even if there is only one quality constraint at each terminal. Further, it is proved that the NP-hardness also persists if the number of sources and the number of terminals are no more than two, and it is proved that the problem remains hard if all in-degrees or all out-degrees are at most two. Examples of special cases in which the problem is solvable by linear programming are also given. Finally, some open problems, which need to be addressed in order to identify more closely the borderlines between polynomially solvable and NP-hard variants of the pooling problem, are pointed out.     

On complexity of Minimum Leaf Out-Branching problem

Given a digraph D, the Minimum Leaf Out-Branching problem (MinLOB) is the problem of finding in D an out-branching with the minimum possible number of leaves, i.e., vertices of out-degree zero. Gutin, Razgon and Kim [G. Gutin, I. Razgon, E.J. Kim, Minimum leaf out-branching problems, in: Proc. 4th International Conference on Algorithmic Aspects in Information and Management, AAIM’08, in: Lect. Notes Comput. Sci., vol. 5034 2008, pp. 235-246] proved that MinLOB is polynomial time solvable for acyclic digraphs which are exactly the digraphs of directed path-width (DAG-width, directed tree-width, respectively) 0. We investigate how much one can extend this polynomiality result. We prove that already for digraphs of directed path-width (directed tree-width, DAG-width, respectively) 1, MinLOB is NP-hard. On the other hand, we show that for digraphs of restricted directed tree-width (directed path-width, DAG-width, respectively) and a fixed integer k, the problem of checking whether there is an out-branching with at most k leaves is polynomial time solvable.     

The counting complexity of a simple scheduling problem

Let T be a set of tasks. Each task has a non-negative processing time and a deadline. The problem of determining whether or not there is a schedule of the tasks in T such that a single machine can finish processing each of them before its deadline is polynomially solvable. We prove that counting the number of schedules satisfying this condition is #P-complete.     

On the complexity of rainbow spanning forest problem

Given a graph \(G=(V,E,L)\) and a coloring function \(\ell : E \rightarrow L\), that assigns a color to each edge of G from a finite color set L, the rainbow spanning forest problem (RSFP) consists of finding a rainbow spanning forest of G such that the number of components is minimum. A spanning forest is rainbow if all its components (trees) are rainbow. A component whose edges have all different colors is called rainbow component. The RSFP on general graphs is known to be NP-complete. In this paper we use the 3-SAT Problem to prove that the RSFP is NP-complete on trees and we prove that the problem is solvable in polynomial time on paths, cycles and if the optimal solution value is equal to 1. Moreover, we provide an approximation algorithm for the RSFP on trees and we show that it approximates the optimal solution within 2.     

On the complexity of the car sequencing problem

In this note we give an easier proof of the known result that the car sequencing problem is NP-hard, and point out that it is NP-hard in the strong sense. We show that a previous claim of NP-completeness is incorrect, and instead we give a sufficient condition of membership of NP. We also provide a pseudo-polynomial algorithm for a special case.     

On the complexity of a bundle pricing problem

We consider the problem of pricing items in order to maximize the revenue obtainable from a set of single minded customers. We relate the tractability of the problem to structural properties of customers’ valuations: the problem admits an efficient approximation algorithm, parameterized along the inhomogeneity of the valuations.     

On the complexity of the disjoint paths problem

In this paper we consider the disjoint paths problem. Given a graphG and a subsetS of the edge-set ofG the problem is to decide whether there exists a family of disjoint circuits inG each containing exactly one edge ofS such that every edge inS belongs to a circuit inC. By a well-known theorem of P. Seymour the edge-disjoint paths problem is polynomially solvable for Eulerian planar graphsG. We show that (assumingPNP) one can drop neither planarity nor the Eulerian condition onG without losing polynomial time solvability. We prove theNP-completeness of the planar edge-disjoint paths problem by showing theNP-completeness of the vertex disjoint paths problem for planar graphs with maximum vertex-degree three. This disproves (assumingPNP) a conjecture of A. Schrijver concerning the existence of a polynomial time algorithm for the planar vertex-disjoint paths problem. Furthermore we present a counterexample to a conjecture of A. Frank. This conjecture would have implied a polynomial algorithm for the planar edge-disjoint paths problem. Moreover we derive a complete characterization of all minorclosed classes of graphs for which the disjoint paths problem is polynomially solvable. Finally we show theNP-completeness of the half-integral relaxation of the edge-disjoint paths problem. This implies an answer to the long-standing question whether the edge-disjoint paths problem is polynomially solvable for Eulerian graphs.Supported by Sonderforschungsbereich 303 (DFG)     

Super-stationary set, subword problem and the complexity

Let Ω⊂{0,1}^N be a nonempty closed set with N={0,1,2,…}. For N={N₀<N₁<N₂<?}⊂N and ω∈{0,1}^N, define ω[N]∈{0,1}^N by and

     

The parameterized complexity of the induced matching problem

Given a graph G and an integer k≥0, the NP-complete Induced Matching problem asks whether there exists an edge subset M of size at least k such that M is a matching and no two edges of M are joined by an edge of G. The complexity of this problem on general graphs, as well as on many restricted graph classes has been studied intensively. However, other than the fact that the problem is W[1]-hard on general graphs, little is known about the parameterized complexity of the problem in restricted graph classes. In this work, we provide first-time fixed-parameter tractability results for planar graphs, bounded-degree graphs, graphs with girth at least six, bipartite graphs, line graphs, and graphs of bounded treewidth. In particular, we give a linear-size problem kernel for planar graphs.     

ON THE COMPUTATIONAL COMPLEXITY OF THE MAXIMUM TRADE PROBLEM

ＯＮＴＨＥＣＯＭＰＵＴＡＴＩＯＮＡＬＣＯＭＰＬＥＸＩＴＹＯＦＴＨＥＭＡＸＩＭＵＭＴＲＡＤＥＰＲＯＢＬＥＭＺ．－Ｑ．Ｌｕｏ；Ｄ．Ｌ．ＰＡＲＮＡＳ（ＣｏｍｍｕｎｉｃａｔｉｏｎｓＲｅｓｅａｒｃｈＬａｂｏｒａｔｏｃｙＤｅｐａｒｔｍｅｎｔｏｆＥｌｅｃｔｒｉｃａ...     

The pricing problem. Part II: Computational complexity

In this paper, we show that the problem under study is in the class Log-APX, cannot be approximate with absolute error bounded by a constant, and the associated evaluation problem is nontrivial in the class Δ ₂ ^p . The two cases of the problem solvable in polynomial time are provided.     

On the complexity of an optimal routing tree problem

A routing tree for a set of tasks is a decision tree which assigns the tasks to their destinations according to the features of the tasks. A weighted routing tree is one with costs attached to each link of the tree. Links of the same feature have the same cost. It is proved that the problem of finding a routing tree of the minimum cost for a given set of tasks of two features is NP-complete.This research was supported in part by theNSF grantsDCR-8501226 andDCR-8696135. Part of this work was done while the first author was at the Mathematical Sciences Research Institute, Berkeley, California, and while the second author was at the Department of Mathematics, University of California, Santa Barbara, California.     

On the computational complexity of a merge recognition problem

A problem arising from the work of C.A.R. Hoare on parallel programming is that of deciding whether a given string ? is a “merge” of two other given strings σ and τ. We describe a polynomial time algorithm for this problem. This algorithm can easily be extended to check, in polynomial time, whether ? is a merge of any fixed number of strings. The problem for an arbitrary number of strings is shown to be NP-complete and so is unlikely to have a polynomial time algorithm.