Displaying similar documents to “New algorithms for coupled tasks scheduling – a survey”

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...

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, ...

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 : ′ =  ...

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 sparse dynamic programming algorithm for alignment with non-overlapping inversions

Alair Pereira do Lago, Ilya Muchnik, Casimir Kulikowski (2010)

RAIRO - Theoretical Informatics and Applications

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Alignment of sequences is widely used for biological sequence comparisons, and only biological events like mutations, insertions and deletions are considered. Other biological events like inversions are not automatically detected by the usual alignment algorithms, thus some alternative approaches have been tried in order to include inversions or other kinds of rearrangements. Despite many important results in the last decade, the complexity of the problem of alignment with inversions...

An Improved Algorithm for a Bicriteria Batching Scheduling Problem

Cheng He, Xiumei Wang, Yixun Lin, Yundong Mu (2013)

RAIRO - Operations Research - Recherche Opérationnelle

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This note is concerned with the bicriteria scheduling problem on a series-batching machine to minimize maximum cost and makespan. An ( ) algorithm has been established previously. Here is an improved algorithm which solves the problem in ( ) time.

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...

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...

About the choice of the variable to unassign in a decision repair algorithm

Cédric Pralet, Gérard Verfaillie (2010)

RAIRO - Operations Research

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The algorithm (Jussien and Lhomme, (2002) 21–45), which has been designed to solve (CSP), can be seen, either (i) as an extension of the classical algorithm with the introduction of a free choice of the variable to which to backtrack in case of inconsistency, or (ii) as a algorithm in the space of the partial consistent variable assignments. or (iii) as a hybridisation between and . Experiments reported in Pralet and Verfailllie (2004) show that some heuristics...

Extension of Reverse Elimination Method Through a Dynamic Management of the Tabu List

Saïd Hanafi, Arnaud Fréville (2010)

RAIRO - Operations Research

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The Reverse Elimination Method (REM) is a dynamic strategy for managing the tabu list. It is based on logical interdependencies between the solutions encountered during recent iterations of the search. REM provides both a necessary and sufficient condition to prevent cycling. The purpose of this paper is first to incorporate in REM a when cycling is unavoidable, thereby assuring the finite convergence of Tabu Search. Secondly, we correct a generalization of REM, the so-called REM-...

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...