Displaying similar documents to “On the hardness of approximating the UET-UCT scheduling problem with hierarchical communications”

New algorithms for coupled tasks scheduling – a survey

Jacek Blazewicz, Grzegorz Pawlak, Michal Tanas, Wojciech Wojciechowicz (2012)

RAIRO - Operations Research - Recherche Opérationnelle

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The coupled tasks scheduling problem is a class of scheduling problems introduced for beam steering software of sophisticated radar devices, called phased arrays. Due to increasing popularity of such radars, the importance of coupled tasks scheduling is constantly growing. Unfortunately, most of the coupled tasks problems are NP-hard, and only a few practically usable algorithms for such problems were found. This paper provides a survey of already known complexity results of various...

Fast approximation of minimum multicast congestion – Implementation VERSUS Theory

Andreas Baltz, Anand Srivastav (2010)

RAIRO - Operations Research

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The problem of minimizing the maximum edge congestion in a multicast communication network generalizes the well-known -hard multicommodity flow problem. We give the presently best theoretical approximation results as well as efficient implementations. In particular we show that for a network with edges and multicast requests, an OPT + exp(1)ln)-approximation can be computed in lnln) time, where  bounds the time for computing an -approximate minimum Steiner tree. Moreover, we present...

Analysis of a near-metric TSP approximation algorithm

Sacha Krug (2013)

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

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The traveling salesman problem (TSP) is one of the most fundamental optimization problems. We consider the -metric traveling salesman problem ( -TSP), , the TSP restricted to graphs satisfying the -triangle inequality ({}) ≤ (({}) + ({})), for some cost function and any three vertices . The well-known path matching Christofides algorithm (PMCA) guarantees an approximation ratio of 3 /2 and is the best known algorithm for the -TSP, for 1 ≤  ≤ 2....

A note on a two dimensional knapsack problem with unloading constraints

Jefferson Luiz Moisés da Silveira, Eduardo Candido Xavier, Flávio Keidi Miyazawa (2013)

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

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In this paper we address the two-dimensional knapsack problem with unloading constraints: we have a bin , and a list of rectangular items, each item with a class value in {1,...,}. The problem is to pack a subset of into , maximizing the total profit of packed items, where the packing must satisfy the unloading constraint: while removing one item , items with higher class values can not block . We present a (4 + )-approximation algorithm when the bin is a square. We also present (3 + )-approximation...

Differential approximation of NP-hard problems with equal size feasible solutions

Jérôme Monnot (2010)

RAIRO - Operations Research

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In this paper, we focus on some specific optimization problems from graph theory, those for which all feasible solutions have an equal size that depends on the instance size. Once having provided a formal definition of this class of problems, we try to extract some of its basic properties; most of these are deduced from the equivalence, under differential approximation, between two versions of a problem  which only differ on a linear transformation of their objective functions. This...

Solving multi-agent scheduling problems on parallel machines with a global objective function

F. Sadi, A. Soukhal, J.-C. Billaut (2014)

RAIRO - Operations Research - Recherche Opérationnelle

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In this study, we consider a scheduling environment with ( ≥ 1) parallel machines. The set of jobs to schedule is divided into disjoint subsets. Each subset of jobs is associated with one agent. The agents compete to perform their jobs on common resources. The objective is to find a schedule that minimizes a global objective function , while maintaining the regular objective function of each agent, , at a level no greater than a fixed value, ...

Bottleneck Capacity Expansion Problems with General Budget Constraints

Rainer E. Burkard, Bettina Klinz, Jianzhong Zhang (2010)

RAIRO - Operations Research

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This paper presents a unified approach for bottleneck capacity expansion problems. In the bottleneck capacity expansion problem, BCEP, we are given a finite ground set , a family of feasible subsets of and a nonnegative real capacity ĉ for all . Moreover, we are given monotone increasing cost functions for increasing the capacity of the elements as well as a budget . The task is to determine new capacities c ≥ ĉ such that the objective function given by...

Computing and proving with pivots

Frédéric Meunier (2013)

RAIRO - Operations Research - Recherche Opérationnelle

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A simple idea used in many combinatorial algorithms is the idea of . Originally, it comes from the method proposed by Gauss in the 19th century for solving systems of linear equations. This method had been extended in 1947 by Dantzig for the famous simplex algorithm used for solving linear programs. From since, a pivoting algorithm is a method exploring subsets of a ground set and going from one subset to a new one ′ by deleting an element inside and adding an element outside : ′ =  ...

Minimizing the Earliness and Tardiness Cost of a Sequence of Tasks on a Single Machine

Philippe Chrétienne (2010)

RAIRO - Operations Research

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Assume that tasks must be processed by one machine in a fixed sequence. The processing time, the preferred starting time and the earliness and tardiness costs per time unit are known for each task. The problem is to allocate each task a starting time such that the total cost incurred by the early and tardy tasks is minimum. Garey have proposed a nice log) algorithm for the special case of symmetric and task-independent costs. In this paper we first extend that algorithm to...

On the Average Case Complexity of Some P-complete Problems

Maria Serna, Fatos Xhafa (2010)

RAIRO - Theoretical Informatics and Applications

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We show that some classical P-complete problems can be solved efficiently in NC. The probabilistic model we consider is the sample space of input descriptions of the problem with the underlying distribution being the uniform one. We present parallel algorithms that use a polynomial number of processors and have expected time upper bounded by ( ln 4 + (1))log , asymptotically with high probability, where is the instance size.

Square-root rule of two-dimensional bandwidth problem

Lan Lin, Yixun Lin (2011)

RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications

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The bandwidth minimization problem is of significance in network communication and related areas. Let be a graph of vertices. The two-dimensional bandwidth () of is the minimum value of the maximum distance between adjacent vertices when is embedded into an  ×  grid in the plane. As a discrete optimization problem, determining () is NP-hard in general. However, exact results for this parameter can be derived for some special classes of graphs. This...

Inequality-sum: a global constraint capturing the objective function

Jean-Charles Régin, Michel Rueher (2010)

RAIRO - Operations Research

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This paper introduces a new method to prune the domains of the variables in constrained optimization problems where the objective function is defined by a sum , and where the integer variables are subject to difference constraints of the form . An important application area where such problems occur is deterministic scheduling with the as optimality criteria. This new constraint is also more general than a sum constraint defined on a set of ordered variables. Classical...