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A Genetic Algorithm for the Single Machine Maximum Lateness Problem

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  • V. SELS

    ()

  • M. VANHOUCKE

    ()

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    Abstract

    We consider the problem of scheduling a number of jobs, each job having a release time, a processing time and a due date, on a single machine with the objective of minimizing the maximum lateness or tardiness. This problem often occurs as a sub-problem in solving other scheduling environments such as flow shops or job shops. We developed a genetic algorithm and compared its performance with alternative methods on diverse data sets. Based on a literature study on genetic algorithms in single machine scheduling, a fair comparison of genetic operators was made. We performed an extensive study of local search algorithms, based on the trade-off between the intensification and diversification strategy. Computational results further revealed that combining different neighborhoods in an intelligent manner can remarkably improve the solution quality.

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    Bibliographic Info

    Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 09/613.

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    Length: 2 pages
    Date of creation: Sep 2009
    Date of revision:
    Handle: RePEc:rug:rugwps:09/613

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