We present a fast polynomial-time algorithm for single-machine scheduling problem with release times (r(j)), processing times (p(j)) and due dates (d(j)) with the objective to minimize the maximum job lateness. The ge...
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We present a fast polynomial-time algorithm for single-machine scheduling problem with release times (r(j)), processing times (p(j)) and due dates (d(j)) with the objective to minimize the maximum job lateness. The general setting is strongly NP-hard. We expose a particular embedded structure that typically possess a subset of jobs in an instance of the problem. We establish useful properties of the problem instances that tolerate this structure, i.e., in such an instance no subset of embedded jobs overlaps in time with the jobs that do not belong to that subset. Relying on these properties, our algorithm finds an optimal solution for the corresponding class of problem instances. Whether a given problem instance is tolerant of the revealed embedded structure becomes known during the execution of the algorithm. Nevertheless, some sufficient conditions in terms of job parameters can a priori be given. One such a condition is that for any pair of jobs j and i with r(i) > r(j) and d(i) < d(j), d(i) - r(j) - p(j) <= d(i) - r(i) - p(i), and if r(i) + p(i) >= r(j) + p(j), then d(i) >= d(j). As we show, our setting remains powerful enough to model important real-life applications. (C) 2019 Elsevier B.V. All rights reserved.
User association is necessary in dense millimeter wave (mmWave) networks to determine which base station a user connects to in order to balance base station loads and maximize a network utility. Given that mmWave conn...
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User association is necessary in dense millimeter wave (mmWave) networks to determine which base station a user connects to in order to balance base station loads and maximize a network utility. Given that mmWave connections are highly directional and vulnerable to small channel variations, user association changes these connections and hence significantly affects the network interference and consequently the users' instantaneous rates. In this paper, we introduce a new load balancing user association scheme for mmWave MIMO cellular networks which consider these dependencies. We formulate the user association problem as mixed integer nonlinear programming and design a polynomial-time algorithm, called worst connection swapping (WCS), to find a near-optimal solution. Simulation results confirm that the proposed user association scheme improves network performance significantly by adjusting the interference according to the association, and under the max-min fairness, also enhances cell-edge users' transmission rates. We also show how the proposed algorithm can be applied under mobility. Furthermore, the proposed WCS algorithm outperforms other generic algorithms for combinatorial programming such as the genetic algorithm in both accuracy and speed at several orders of magnitude faster, and for small networks, where exhaustive search is possible, it reaches the optimal solution.
The DOMINATING INDUCED MATCHING problem, also known as EFFICIENT EDGE DOMINATION, is the problem of determining whether a graph has an induced matching that dominates every edge of the graph. This problem is known to ...
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The DOMINATING INDUCED MATCHING problem, also known as EFFICIENT EDGE DOMINATION, is the problem of determining whether a graph has an induced matching that dominates every edge of the graph. This problem is known to be NP-complete. We study the computational complexity of the problem in special graph classes. In the present paper, we identify a critical class for this problem (i.e., a class lying on a "boundary" separating difficult instances of the problem from polynomially solvable ones) and derive a number of polynomial-time results. In particular, we develop polynomial-time algorithms to solve the problem for claw-free graphs and convex graphs. (C) 2010 Elsevier B.V. All rights reserved.
A function f : V( G) ->{0, 1, 2} is called a Roman dominating function on G = ( V(G), E(G)) if for every vertex v with f (v) = 0, there exists a vertex u epsilon N-G(v) such that f (u) = 2. A function f : V(G). {0,...
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A function f : V( G) ->{0, 1, 2} is called a Roman dominating function on G = ( V(G), E(G)) if for every vertex v with f (v) = 0, there exists a vertex u epsilon N-G(v) such that f (u) = 2. A function f : V(G). {0, 1, 2} induces an ordered partition ( V-0, V-1, V-2) of V( G), where V-i = {v epsilon V( G) : f (v) = i} for i epsilon{0, 1, 2}. A function f : V(G)->{0, 1, 2} with ordered partition ( V-0, V-1, V-2) is called a unique response Roman function if for every vertex v with f (v) = 0, | N-G(v) boolean AND V-2| <= 1, and for every vertex v with f (v) = 1 or 2, | N-G(v) boolean AND V-2| = 0. A function f : V(G)->{0, 1, 2} is called a unique response Roman dominating function (URRDF) on G if it is a unique response Roman function as well as a Roman dominating function on G. The weight of a unique response Roman dominating function f is the sum f ( V(G)) = Sigma (v epsilon V(G)) f (v), and the minimum weight of a unique response Roman dominating function on G is called the unique response Roman domination number of G and is denoted by u(R)(G). Given a graph G, the Min- URRDF problem asks to find a unique response Roman dominating function of minimum weight on G. In this paper, we study the algorithmic aspects of Min- URRDF. We show that the decision version of Min- URRDF remains NP-complete for chordal graphs and bipartite graphs. We show that for a given graph with n vertices, Min- URRDF cannot be approximated within a ratio of n(1-epsilon) for any epsilon > 0 unless P = NP. We also show that Min- URRDF can be approximated within a factor of Delta + 1 for graphs having maximum degree Delta. On the positive side, we design a linear-timealgorithm to solve Min- URRDF for distance-hereditary graphs. Also, we show that Min- URRDF is polynomial-time solvable for interval graphs, and strengthen the result by showing that Min- URRDF can be solved in linear-time for proper interval graphs, a proper subfamily of interval graphs.
We consider several extensions of the fractional bin packing problem, a relaxation of the traditional bin packing problem where the objects may be split across multiple bins. In these extensions, we introduce load-bal...
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We consider several extensions of the fractional bin packing problem, a relaxation of the traditional bin packing problem where the objects may be split across multiple bins. In these extensions, we introduce load-balancing constraints imposing that the share of each object which is assigned to a same bin must be equal. We propose a Mixed-Integer Programming (MIP) formulation and show that the problem becomes NP-hard if we limit to at most 3 the number of bins across which each object can be split. We then consider a variant where the balanced allocations of objects to bins may be done in successive rounds;this problem was inspired by telecommunication applications, and may be used to model simple Live Streaming networks. We show that two rounds are always sufficient to completely assign all objects to the bins and then provide an optimal polynomial-time allocation algorithm for this problem. (C) 2018 Elsevier B.V. All rights reserved.
We prove that on the class of (P-6, diamond)-free graphs the Maximum-Weight Independent Set problem and the Minimum-Weight Independent Dominating Set problem can be solved in polynomialtime.
We prove that on the class of (P-6, diamond)-free graphs the Maximum-Weight Independent Set problem and the Minimum-Weight Independent Dominating Set problem can be solved in polynomialtime.
The paper deals with an inverse problem of reconstructing matrices from their marginal sums. More precisely, we are interested in the existence of rxsmatrices for which only the following information is available: The...
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The paper deals with an inverse problem of reconstructing matrices from their marginal sums. More precisely, we are interested in the existence of rxsmatrices for which only the following information is available: The entries belong to known subsets of c distinguishable abelian groups, and the row and column sums of all entries from each group are given. This generalizes Ryser's classical problem of characterizing the set of all 0-1-matrices with given row and column sums and is a basic problem in (polyatomic) discrete tomography. We show that the problem is closely related to packings of trees in bipartite graphs, prove consistency results, give algorithms and determine its complexity. In particular, we find a somewhat unusual complexity behavior: the problem is hard for "small" but easy for "large" matrices.
This paper gives various (positive and negative) results on the complexity of the problem of computing and approximating mixed volumes of polytopes and more general convex bodies in arbitrary dimension. On the negativ...
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This paper gives various (positive and negative) results on the complexity of the problem of computing and approximating mixed volumes of polytopes and more general convex bodies in arbitrary dimension. On the negative side, we present several # P-hardness results that focus on the difference of computing mixed volumes versus computing the volume of polytopes. We show that computing the volume of zonotopes is # P-hard (while each corresponding mixed volume can be computed easily) but also give examples showing that computing mixed volumes is hard even when computing the volume is easy. On the positive side, we derive a randomized algorithm for computing the mixed volumes [GRAPHICS] of well-presented convex bodies K(1),...,K(s), where m(1),...,m(s) is an element of N(0) and m(1) greater than or equal to n - psi(n) with psi(n) = o(log n/log log n). The algorithm is an interpolation method based on polynomial-time randomized log algorithms for computing the volume of convex bodies. This paper concludes with applications of our results to various problems in discrete mathematics, combinatorics, computational convexity, algebraic geometry, geometry of numbers, and operations research.
Ancestral graphs can encode conditional independence relations that arise in directed acyclic graph (DAG) models with latent and selection variables. However, for any ancestral graph, there may be several other graphs...
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Ancestral graphs can encode conditional independence relations that arise in directed acyclic graph (DAG) models with latent and selection variables. However, for any ancestral graph, there may be several other graphs to which it is Markov equivalent. We state and prove conditions under which two maximal ancestral graphs are Markov equivalent to each other, thereby extending analogous results for DAGs given by other authors. These conditions lead to an algorithm for determining Markov equivalence that runs in time that is polynomial in the number of vertices in the graph.
A strong clique in a graph is a clique intersecting every maximal independent set. We study the computational complexity of six algorithmic decision problems related to strong cliques in graphs and almost completely d...
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A strong clique in a graph is a clique intersecting every maximal independent set. We study the computational complexity of six algorithmic decision problems related to strong cliques in graphs and almost completely determine their complexity in the classes of chordal graphs, weakly chordal graphs, line graphs and their complements, and graphs of maximum degree at most three. Our results rely on connections with matchings and relate to several graph properties studied in the literature, including well-covered graphs, localizable graphs, and general partition graphs. (C) 2019 Published by Elsevier B.V.
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