@article {3340,
	title = {A New Genetic Algorithm or the Flexible Job Shop scheduling problems, ISSN/ISBN 1738-494X / 1976-3824},
	journal = {J MECH SCI TECHNOL},
	volume = {Volume 29},
	number = {Issue 3},
	year = {2015},
	pages = { pp 1273{\textendash}1281},
	abstract = {Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.},
	url = {https://link.springer.com/article/10.1007/s12206-015-0242-7},
	author = {Driss Imen and Mouss kinza Nadia and Laggoun Assia}
}
