{"title":"Using Genetic Algorithms to Outline Crop Rotations and a Cropping-System Model","authors":"Nicolae Bold, Daniel Nijloveanu","volume":114,"journal":"International Journal of Computer and Information Engineering","pagesStart":1028,"pagesEnd":1033,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10004534","abstract":"The idea of cropping-system is a method used by
\r\nfarmers. It is an environmentally-friendly method, protecting the
\r\nnatural resources (soil, water, air, nutritive substances) and increase
\r\nthe production at the same time, taking into account some crop
\r\nparticularities. The combination of this powerful method with the
\r\nconcepts of genetic algorithms results into a possibility of generating
\r\nsequences of crops in order to form a rotation. The usage of this type
\r\nof algorithms has been efficient in solving problems related to
\r\noptimization and their polynomial complexity allows them to be used
\r\nat solving more difficult and various problems. In our case, the
\r\noptimization consists in finding the most profitable rotation of
\r\ncultures. One of the expected results is to optimize the usage of the
\r\nresources, in order to minimize the costs and maximize the profit. In
\r\norder to achieve these goals, a genetic algorithm was designed. This
\r\nalgorithm ensures the finding of several optimized solutions of
\r\ncropping-systems possibilities which have the highest profit and,
\r\nthus, which minimize the costs. The algorithm uses genetic-based
\r\nmethods (mutation, crossover) and structures (genes, chromosomes).
\r\nA cropping-system possibility will be considered a chromosome and
\r\na crop within the rotation is a gene within a chromosome. Results
\r\nabout the efficiency of this method will be presented in a special
\r\nsection. The implementation of this method would bring benefits into
\r\nthe activity of the farmers by giving them hints and helping them to
\r\nuse the resources efficiently.","references":"[1] Francis, C. A., Multiple cropping systems, Macmillan Publishing\r\nCompany, New York, USA, 1986.\r\n[2] D. A. Popescu, N. Bold, A. C. Bold, An algorithm based on the\r\nbacktracking method for cropping-systems and the rotation of cultures,\r\nThe 9th International Conference INTER-ENG 2015 - Interdisciplinarity\r\nin Engineering, 8 - 9 October, \"Petru Maior\" University of T\u00eergu-Mure\u015f,\r\nRomania, 2015\r\n[3] D. Nijloveanu, N. Bold, A Random Algorithm for Generating Cropping\r\n\u2013 System Possibilities, The 10th International Conference on Virtual\r\nLearning, Timi\u015foara, Romania, October 2015\r\n[4] S. S. Snapp, S. M. Swinton, R. Labarta, D. Mutch, J. R. Black, R. Leep,\r\nJ. Nyiraneza and K. O'Neil Evaluating Cover Crops for Benefits, Costs\r\nand Performance within Cropping System Niches, Agronomy Journal,\r\nVol. 97, No. 1, p. 322-332, 2004.\r\n[5] C. Nicolae, Rotatia culturilor, mijloc eficient de sporire a fertilitatii si a\r\nproductiei agricole pe solurile acide, Probleme agricole, Bucharest, 1971\r\n[6] Benyamin Khoshnevisan, Elham Bolandnazar, Shahaboddin\r\nShamshirband, Hanifreza Motamed Shariati, Nor Badrul Anuar, Miss\r\nLaiha Mat Kiah, Decreasing environmental impacts of cropping systems\r\nusing life cycle assessment (LCA) and multi-objective genetic\r\nalgorithm, Journal of Cleaner Production, Volume 86, Pages 67\u201377, 1\r\nJanuary 2015.\r\n[7] Apostolos Perifanos, Petru Gu\u0219, Teodor Rusu, Simona Chetan,\r\nResearches regarding the role of crop rotation and unconventional soil\r\ntillage in sustainable agriculture, The 6th International Symposium Soil\r\nMinimum Tillage Systems, p. 146-158, Cluj-Napoca, 27-29 June 2011.\r\n[8] C.A. Francis, J.H. Sanders, Economic analysis of bean and maize\r\nsystems: monoculture versus associated cropping, Field Crops Research,\r\nVolume 1, Pages 319-335, 1978.\r\n[9] T. A. Delbridge, Jeffrey A. Coulter, Robert P. King, Craig C. Sheaffer\r\nand Donald L. Wyse, Economic Performance of Long-Term Organic\r\nand Conventional Cropping Systems in Minnesota, Agronomy Journal,\r\nVol. 103 No. 5, p. 1372-1382, 2010.\r\n[10] C. O. St\u00f6ckle, M. Donatelli, R. Nelson, CropSyst, a cropping systems\r\nsimulation model, European Journal of Agronomy, Modelling Cropping\r\nSystems: Science, Software and Applications, Volume 18, Issues 3\u20134,\r\nPages 289\u2013307, January 2003\r\n[11] Sin Gheorghe, Partal Elena, Influen\u0163a rota\u0163iei \u015fi a fertiliz\u0103rii asupra\r\nproduc\u0163iilor de gr\u00e2u \u015fi porumb \u00een contextul varia\u0163iilor climatice, AN.\r\nI.N.C.D.A. Fundulea, vol. LXXVIII, nr. l, 2010\r\n[12] C. Gro\u0219an, M. Oltean, Algoritmi Evolutivi, Ginfo, number 8, p. 30-36,\r\nDecember 2011.\r\n[13] D. A. Popescu, D. Radulescu, Monitoring of irrigation systems using\r\ngenetic algorithms, ICMSAO, IEEE Xplorer, pp. 1-4, 2015.\r\n[14] D. A. Popescu, D. Radulescu, Approximately Similarity Measurement of\r\nWeb Sites, ICONIP, Neural Information Processing, LNCS, Springer, 9-\r\n12 November, pp. 624-630, 2015.\r\n[15] D. A. Popescu, D. Nicolae, Generating a class schedule with reduced\r\nnumber of constraints, The 9th International Scientific Conference\r\neLearning and software for Education, Bucharest, April 25-26,\r\nProceedings, pag 297-300, 2013.\r\n[16] D. A. Popescu, Probabilistic program that generates Langford\r\nsequences, Buletin Stiintific - Universitatea din Pitesti, Seria Matematica\r\nsi Informatica, Nr. 12, pg. 129-133, 2006.\r\n[17] Popescu, D. A. and Ionita, A. E. Combinatorica si Teoria Grafurilor, Ed.\r\nRhabon. Tg. Jiu, 2005.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 114, 2016"}