BibTeX:

@article{IJIRSTV3I7037,
     title={Minimization of Make Span of a Flexible Job Shop Problem with the Approach of Genetic Algorithm},
     author={N. Gopikrishna, B. Sathish Kumar, S. Pradeep and V. Thirupathi},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={7},
     pages={106--112},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I7037.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Present paper proposes the Genetic Algorithm which helps in selection of a machine tool for FJSP (flexible job-shop scheduling problems), which may result in reduction of a make span. The genetic algorithm (GA), a class of theoretical search algorithms, which is effective in finding optimal solutions to variety of problems and it comprises as follows: 1) An effective selection method. 2) New crossover operator uses the combination of genes concept. 3) New mutation operator helps in maintaining overcoming premature convergence and population diversity. The aim of this research is to find a schedule that minimizes the “MAKE SPAN”. The experimental results “of 2 jobs 3 operations 3 machine models provided below” proves this phenomena.

Flexible Job-Shop Scheduling Problems (FJSP), Genetic Algorithm (GA), Selection, Crossover, Mutation