Two complexity results on c-optimality in experimental design

Finding a c-optimal design of a regression model is a basic optimization problem in statistics. We study the computational complexity of the problem in the case of a finite experimental domain. We formulate a decision version of the problem and prove its NP\boldsymbol{\mathit{NP}}-completeness. We provide examples of computationally complex instances of the design problem, motivated by cryptography. The problem, being NP\boldsymbol{\mathit{NP}}-complete, is then relaxed; we prove that a decision version of the relaxation, called approximate c-optimality, is P-complete. We derive an equivalence theorem for linear programming: we show that the relaxed c-optimality is equivalent (in the sense of many-one LOGSPACE-reducibility) to general linear programming.     

Co-NP-completeness of some matrix classification problems

The classes of P-, P ₀-, R ₀-, semimonotone, strictly semimonotone, column sufficient, and nondegenerate matrices play important roles in studying solution properties of equations and complementarity problems and convergence/complexity analysis of methods for solving these problems. It is known that the problem of deciding whether a square matrix with integer/rational entries is a P- (or nondegenerate) matrix is co-NP-complete. We show, through a unified analysis, that analogous decision problems for the other matrix classes are also co-NP-complete. Received: April 1999 / Accepted: March 1, 2000?Published online May 12, 2000     

Polar permutation graphs are polynomial-time recognisable

Polar graphs generalise bipartite graphs, cobipartite graphs, and split graphs, and they constitute a special type of matrix partitions. A graph is polar if its vertex set can be partitioned into two, such that one part induces a complete multipartite graph and the other part induces a disjoint union of complete graphs. Deciding whether a given arbitrary graph is polar, is an NP$\text{NP}$-complete problem. Here, we show that for permutation graphs this problem can be solved in polynomial time. The result is surprising, as related problems like achromatic number and cochromatic number are NP$\text{NP}$-complete on permutation graphs. We give a polynomial-time algorithm for recognising graphs that are both permutation and polar. Prior to our result, polarity has been resolved only for chordal graphs and cographs.     

The effectiveness of finite improvement algorithms for finding global optima

This paper investigates the effectiveness of using finite improvement algorithms for solving decision, search, and optimization problems. Finite improvement algorithms operate in a finite number of iterations, each taking a polynomial amount of work, where strict improvement is required from iteration to iteration. The hardware, software, and way of measuring complexity found in the polynomial setting are modified to identify the concept of repetition and define the new classes of decision problems,FI andNFI. A firstNFI-complete problem is given using the idea ofFI-transformations. Results relating these new classes toP, NP, andNP-complete are given. It is shown that if an optimization problem in a new classPGS isNP-hard, thenNP=co-NP. TwoPGS problems are given for which no polynomial algorithms are known to exist.     

Weak convergence in the dual of weak L<Superscript>p</Superscript>

We consider a Dedekind σ-complete Banach lattice E whose dual is weakly sequentially complete. Suppose that E has a positive element u and a family of positive operators $ \mathcal{G} $ \mathcal{G} such that

Minimizing the weighted number of tardy jobs with due date assignment and capacity-constrained deliveries

We study a supply chain scheduling problem, where a common due date is assigned to all jobs and the number of jobs in delivery batches is constrained by the batch size. Our goal is to minimize the sum of the weighted number of tardy jobs, the due-date-assignment costs and the batch-delivery costs. We show that some well-known NP\mathcal{NP}-hard problems reduce to our problem. Then we propose a pseudo-polynomial algorithm for the problem, establishing that it is NP\mathcal{NP}-hard only in the ordinary sense. Finally, we convert the algorithm into an efficient fully polynomial time approximation scheme.     

Maximum transversal in partial Latin squares and rainbow matchings

In a partial Latin square P a set of distinct entries, such that no two of which are in the same row or column is called a transversal. By the size of a transversal T, we mean the number of its entries. We define a duplex to be a partial Latin square of order n containing 2n entries such that exactly two entries lie in each row and column and each of n symbols occurs exactly twice. We show that determining the maximum size of a transversal in a given duplex is an NP-complete problem. This problem relates to independent sets in certain subfamilies of cubic graphs. Generalizing the concept of transversals in edge coloring of graphs we are led to introduce the concept of rainbow matching. We show that if each color appears at most twice then it is a polynomial time problem to know whether there exists a rainbow matching of size at least ⌊n/2⌋-t for each fixed t, where n is the order of the graph. As an application we show that for any fixed t, there is a polynomial time algorithm which decides whether α(G)?n-t, for any graph G on 2n vertices containing a perfect matching. At the end we mention some other applications of rainbow matching.     

Finding the connected components and a maximum clique of an intersection graph of rectangles in the plane

An intersection graph of rectangles in the (x, y)-plane with sides parallel to the axes is obtained by representing each rectangle by a vertex and connecting two vertices by an edge if and only if the corresponding rectangles intersect. This paper describes algorithms for two problems on intersection graphs of rectangles in the plane. One is an O(n log n) algorithm for finding the connected components of an intersection graph of n rectangles. This algorithm is optimal to within a constant factor. The other is an O(n log n) algorithm for finding a maximum clique of such a graph. It seems interesting that the maximum clique problem is polynomially solvable, because other related problems, such as the maximum stable set problem and the minimum clique cover problem, are known to be NP-complete for intersection graphs of rectangles. Furthermore, we briefly show that the k-colorability problem on intersection graphs of rectangles is NP-complete.     

Systems of Polynomials for Detecting Orientable Matroids

We study systems of polynomial equations that correspond to a matroid M. Each of these systems has a zero solution if and only if M is orientable. Since determining if a matroid is orientable is NP-complete with respect to the size of the input data, determining if these systems have solutions is also NP-complete. However, we show that one of the associated polynomial systems corresponding to M is linear if M is a binary matroid and thus it may be determined if binary matroids are orientable in polynomial time given the circuits and cocircuits of said matroid as the input. In the case when M is not binary, we consider the associated system of non-linear polynomials. In this case Hilbertʼs Nullstellensatz gives us that M is non-orientable if and only if a certain certificate to the given polynomials system exists. We wish to place bounds on the degree of these certificates in future research.     

<Emphasis Type="BoldItalic">κ</Emphasis>-Complete Uniquely Complemented Lattices

We show that for any infinite cardinal κ, every complete lattice where each element has at most one complement can be regularly embedded into a uniquely complemented κ-complete lattice. This regular embedding preserves all joins and meets, in particular it preserves the bounds of the original lattice. As a corollary, we obtain that every lattice where each element has at most one complement can be embedded into a uniquely complemented κ-complete lattice via an embedding that preserves the bounds of the original lattice.     

On the Intrinsic Complexity of Elimination Theory

We consider the intrinsic complexity of selected algorithmic problems of classical elimination theory in algebraic geometry. The inputs and outputs of these problems are given by finite sets of polynomials which we represent alternatively in dense form or by straight line programs. We begin with an overview on the known upper bounds for the sequential and parallel time complexity of these problems and show then that in the most important cases these bounds are tight. Our lower bound results include both the relative and the absolute viewpoint of complexity theory. On one side we give reductions of fundamental questions of elimination theory to NP- and P^#-complete problems and on the other side we show that some of these questions may have exponential size outputs. In this way we confirm the intrinsically exponential character of algorithmic problems in elimination theory whatever the type of data structure may be.     

Worst-case complexity bounds for algorithms in the theory of integral quadratic forms

The problem of factoring an integer and many other number-theoretic problems can be formulated in terms of binary quadratic Diophantine equations. This class of equations is also significant in complexity theory, subclasses of it having provided most of the natural examples of problems apparently intermediate in difficulty between P and NP-complete problems, as well as NP-complete problems [2, 3, 22, 26]. The theory of integral quadratic forms developed by Gauss gives some of the deepest known insights into the structure of classes of binary quadratic Diophantine equations. This paper establishes explicit polynomial worst-case running time bounds for algorithms to solve certain of the problems in this theory. These include algorithms to do the following: (1) reduce a given integral binary quadratic form; (2) quasi-reduce a given integral ternary quadratic form; (3) produce a form composed of two given integral binary quadratic forms; (4) calculate genus characters of a given integral binary quadratic form, when a complete prime factorization of its determinant D is given as input; (5) produce a form that is the square root under composition of a given form (when it exists), when a complete factorization of D and a quadratic nonresidue for each prime dividing D is given as input.     

On computational complexity of membership test in flow games and linear production games

Let Γ≡(N,v) be a cooperative game with the player set N and characteristic function v: 2^N→R. An imputation of the game is in the core if no subset of players could gain advantage by splitting from the grand coalition of all players. It is well known that, for the flow game (and equivalently, for the linear production game), the core is always non-empty and a solution in the core can be found in polynomial time. In this paper, we show that, given an imputation x, it is NP-complete to decide x is not a member of the core, for the flow game. And because of the specific reduction we constructed, the result also holds for the linear production game. Received: October 2000/Final version: March 2002     

NP-Complete operations research problems and approximation algorithms

For a large number of discrete optimization problems like the traveling salesman problem, the quadratic assignment problem, the general flow-shop problem, the knapsack problem etc. all known algorithms have the discouraging property that their (worst-case) running times on a computer grow exponentially with the size of the problem. All efforts to find polynomial bounded algorithms for these problems have failed. Recent results in complexity theory show that these problems belong to the classes ofNP-complete orNP-hard problems. It is a common belief that for problems belonging to these classes no polynomial bounded algorithms exist. Heuristics or approximation algorithms should be applied to these problems.The aim of this tutorial paper is to give a survey onNP-complete andNP-hard problems and on approximation algorithms. All concepts introduced are illustrated by examples which are closely related to the knapsack problem and can be understood easily. References to most other problems of interest to operations researchers are given.

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Zusammenfassung Für eine große Anzahl von diskreten Optimierungsproblemen wie das Traveling Salesman Problem, das quadratische Zuordnungsproblem, das allgemeine Flowshop Problem, das Rucksackproblem usw. haben alle bisherigen Lösungsansätze die unangenehme Eigenschaft, daß der Rechenumfang der entsprechenden Algorithmen exponentiell mit dem Umfang der Probleme wächst. Alle Bemühungen polynomial beschränkte Verfahren für solche Probleme zu finden waren bislang ergebnislos. Neuere Ergebnisse der Komplexitätstheorie besagen, daß diese Probleme zu den Klassen derNP-vollständigen bzw.NP-schwierigen Probleme gehören und somit nach allgemein verbreiteter Auffassung wohl niemals polynomial lösbar sein werden. Die Anwendung von heuristischen Verfahren oder approximativen Algorithmen scheint der einzige Ausweg in dieser Situation.Ziel der Arbeit ist es, einen einführenden Uberblick über die Theorie derNP-vollständigen undNP-schwierigen Probleme sowie über approximative Verfahren zu geben. Alle in der Arbeit einge-führten Begriffe werden an einfach verständlichen Beispielen erläutert, die eng mit dem Rucksack-problem verwandt sind.Für weitere Probleme, die den Unternehmensforscher interessieren, findet der Leser ausführliche Literaturübersichten.

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An invited survey.     

Vertex transversals that dominate

For any graph, there is a largest integer k such that given any partition of the vertex set with at most k elements in each class of the partition, there is transversal of the partition that is a dominating set in the graph. Some basic results about this parameter, the partition domination number, are obtained. In particular, it is shown that its value is 2 for the two-dimensional infinite grid, and that determining whether a given vertex partition admits a dominating transversal is NP-complete, even for a graph which is a simple path. The existence of various dominating transversals in certain partitions in regular graphs is studied as well. © 1996 John Wiley & Sons, Inc.     

On the Multiplicative Complexity of the Inversion and Division of Hamiltonian Quaternions

The multiplicative complexity of a finite set of rational functions is the number of essential multiplications and divisions that are necessary and sufficient to compute these rational functions. We prove that the multiplicative complexity of inversion in the division algebra \H of Hamiltonian quaternions over the reals, that is, the multiplicative complexity of the coordinates of the inverse of a generic element from \H , is exactly eight. Furthermore, we show that the multiplicative complexity of the left and right division of Hamiltonian quaternions is at least eleven. July 17, 2001. Final version received: October 8, 2001.     

On a bipartition problem of Bollobás and Scott

The bipartite density of a graph G is max {|E(H)|/|E(G)|: H is a bipartite subgraph of G}. It is NP-hard to determine the bipartite density of any triangle-free cubic graph. A biased maximum bipartite subgraph of a graph G is a bipartite subgraph of G with the maximum number of edges such that one of its partite sets is independent in G. Let $ \mathcal{H} $ \mathcal{H} denote the collection of all connected cubic graphs which have bipartite density $ \tfrac{4} {5} $ \tfrac{4} {5} and contain biased maximum bipartite subgraphs. Bollobás and Scott asked which cubic graphs belong to $ \mathcal{H} $ \mathcal{H} . This same problem was also proposed by Malle in 1982. We show that any graph in $ \mathcal{H} $ \mathcal{H} can be reduced, through a sequence of three types of operations, to a member of a well characterized class. As a consequence, we give an algorithm that decides whether a given graph G belongs to $ \mathcal{H} $ \mathcal{H} . Our algorithm runs in polynomial time, provided that G has a constant number of triangles that are not blocks of G and do not share edges with any other triangles in G.     

Complexity results on restricted instances of a paint shop problem for words

We study the following problem: an instance is a word with every letter occurring twice. A solution is a 2-coloring of its letters such that the two occurrences of every letter are colored with different colors. The goal is to minimize the number of color changes between adjacent letters.This is a special case of the paint shop problem for words, which was previously shown to be NP-complete. We show that this special case is also NP-complete and even APX-hard. Furthermore, derive lower bounds for this problem and discuss a transformation into matroid theory enabling us to solve some specific instances within polynomial time.