Volume 7 Issue 1 - May 2016

  • 1. Flow shop scheduling using genetic algorithm

    Authors : Vinoj K, Tijo Jose

    Pages : 231-239

    DOI : http://dx.doi.org/10.21172/1.71.033

    Keywords : Mean flow time, genetic algorithm, single-point crossover, shift mutation

    Abstract :

    A flow shop is a production system in which machines are arranged in the order in which operations are performed on jobs. The flow shop is characterized by a flow of work that is unidirectional. The problem of scheduling in a flow-shop is considered in the present work with the objective of minimizing mean flow time. Mean flow time is average of the completion time of all jobs. In the present work, genetic algorithm (GA) is used for the solution of the flow shop scheduling problem. Small size and large size problems are considered for the experiments. The performance of a genetic algorithm depends very much on the selection of the proper genetic operators. The various genetic operators such as single-point crossover with shift mutation, single-point crossover with random exchange mutation, two-point crossover with shift mutation, two-point crossover with random exchange mutation are examined. It is found that GA with two-point crossover and shift mutation operator provides better solutions in many of the problems considered in the present work.

    Citing this Journal Article :

    Vinoj K, Tijo Jose, "Flow shop scheduling using genetic algorithm", https://www.ijltet.org/journal_details.php?id=901&j_id=3049, Volume 7 Issue 1 - May 2016, 231-239, #ijltetorg