140 research outputs found

    On Games corresponding to Sequencing Situations with Precedence Relations

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    In this paper we study a class of cooperative sequencing games that arise from one-machine sequencing situations in which chain precedence relations are imposed on the jobs. It is shown that these sequencing games are convex.cooperative games, sequencing situations, convexity

    On the Convexity of Precedence Sequencing Games

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    In this paper we study a class of cooperative sequencing games that arise from one-machine sequencing situations in which chain precedence relations are imposed on the jobs.It is shown that these sequencing games are convex.cooperative games;sequencing games

    How the structure of precedence constraints may change the complexity class of scheduling problems

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    This survey aims at demonstrating that the structure of precedence constraints plays a tremendous role on the complexity of scheduling problems. Indeed many problems can be NP-hard when considering general precedence constraints, while they become polynomially solvable for particular precedence constraints. We also show that there still are many very exciting challenges in this research area

    Single-machine scheduling with deteriorating jobs under a series-parallel graph constraint

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    Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

    On the Convexity of Precedence Sequencing Games

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    In this paper we study a class of cooperative sequencing games that arise from one-machine sequencing situations in which chain precedence relations are imposed on the jobs.It is shown that these sequencing games are convex

    Machine scheduling with precedence constraints : (preprint)

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    Stronger Lagrangian bounds by use of slack variables: applications to machine scheduling problems

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    Lagrangian relaxation is a powerful bounding technique that has been applied successfully to manyNP-hard combinatorial optimization problems. The basic idea is to see anNP-hard problem as an easy-to-solve problem complicated by a number of nasty side constraints. We show that reformulating nasty inequality constraints as equalities by using slack variables leads to stronger lower bounds. The trick is widely applicable, but we focus on a broad class of machine scheduling problems for which it is particularly useful. We provide promising computational results for three problems belonging to this class for which Lagrangian bounds have appeared in the literature: the single-machine problem of minimizing total weighted completion time subject to precedence constraints, the two-machine flow-shop problem of minimizing total completion time, and the single-machine problem of minimizing total weighted tardiness
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