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Minimising mean squared deviation of job completion times about a common due date in multimachine systems
Published in
2011
Volume: 5
   
Issue: 4
Pages: 424 - 447
Abstract
In this paper we consider the problem of scheduling n jobs on two identical parallel machines in order to minimise the mean squared deviation (MSD) of job completion times about a given common due date. When due dates are small and large deviations of job completion times from the due dates are undesirable, it becomes necessary to consider parallel machines. MSD comes under the category of non-regular performance measures, which penalises jobs that are early as well as late. In this paper we develop a lower bound on MSD for a given partial schedule and present a branch and bound algorithm to solve the problem. Optimal solutions for problem instances up to 35 jobs have been obtained for different values of due dates and the results of computational testing are presented. Based on our experiments we observe that when the due date exceeds a certain value the second machine becomes undesirable. We also propose a heuristic to provide quick solutions for problems of larger size. Copyright © 2011 Inderscience Enterprises Ltd.
About the journal
JournalEuropean Journal of Industrial Engineering
ISSN17515254
Open AccessNo
Concepts (21)
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    Branch and bounds
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    Branch-and-bound algorithms
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    COMMON DUE DATE
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    COMPUTATIONAL TESTING
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    DUE DATES
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    IDENTICAL PARALLEL MACHINES
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    JOB COMPLETION
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    Large deviations
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    Lower bounds
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    MEAN SQUARED DEVIATION
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    MSD
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    MULTI MACHINE SCHEDULING
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    Multimachine systems
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    Optimal solutions
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    PARALLEL MACHINE
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    Performance measure
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    Problem instances
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    Algorithms
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    BUSINESS MACHINES
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    Linear programming
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    Problem solving