@article{(Open Science Index):https://publications.waset.org/pdf/10004534,
	  title     = {Using Genetic Algorithms to Outline Crop Rotations and a Cropping-System Model},
	  author    = {Nicolae Bold and  Daniel Nijloveanu},
	  country	= {},
	  institution	= {},
	  abstract     = {The idea of cropping-system is a method used by
farmers. It is an environmentally-friendly method, protecting the
natural resources (soil, water, air, nutritive substances) and increase
the production at the same time, taking into account some crop
particularities. The combination of this powerful method with the
concepts of genetic algorithms results into a possibility of generating
sequences of crops in order to form a rotation. The usage of this type
of algorithms has been efficient in solving problems related to
optimization and their polynomial complexity allows them to be used
at solving more difficult and various problems. In our case, the
optimization consists in finding the most profitable rotation of
cultures. One of the expected results is to optimize the usage of the
resources, in order to minimize the costs and maximize the profit. In
order to achieve these goals, a genetic algorithm was designed. This
algorithm ensures the finding of several optimized solutions of
cropping-systems possibilities which have the highest profit and,
thus, which minimize the costs. The algorithm uses genetic-based
methods (mutation, crossover) and structures (genes, chromosomes).
A cropping-system possibility will be considered a chromosome and
a crop within the rotation is a gene within a chromosome. Results
about the efficiency of this method will be presented in a special
section. The implementation of this method would bring benefits into
the activity of the farmers by giving them hints and helping them to
use the resources efficiently.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {10},
	  number    = {6},
	  year      = {2016},
	  pages     = {1028 - 1032},
	  ee        = {https://publications.waset.org/pdf/10004534},
	  url   	= {https://publications.waset.org/vol/114},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 114, 2016},
	}