Job Shop Scheduling Problems

presents an efficient genetic algorithm for
solving job shop scheduling problems. A schedule is
encoded by a list of job sequences on machines. This
paper introduces a characteristics preserving
crossover named the subsequence exchange
crossover (SXX). The SXX exchanges subsequences
in parents on each machine when they consist of the
same set of jobs. Schedules generated by SXX are
modified by the Giffler and Thompsom method to
transform into active schedules. An empirical
experiment shows that the proposed method can
produce optimal solutions at a high percentage for
Fisher’s and Thompson’s 10x10 benchmark problem

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Wed, 13/04/2011 - 10:29