Subject Areas : IT Strategy
1 - University of Birjand
Keywords:
Abstract :
References:
[1]. S.A. Mirjalili, "The Ant Lion Optimizer", Advances in Engineering Software , Vol. 83 , pp. 80–98, 2015.
[2]. F. MiarNaeimi, G.R. Azizyan, M. Rashki, "Horse herd optimization algorithm: A nature-inspired algorithm for high-dimensional optimization problems", Knowledge-Based Systems, Vol. 213, pp. 1-17, 2021.
[3]. J.H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, MIT press, 1992.
[4]. J.R. Koza, Genetic Programming: On the Programming of Computers By Means of Natural Selection, MIT press, 1992.
[5]. F. Glover, "Tabu search—Part I" , ORSA J. Comput. Vol. 1, No. 3, pp.190–206, 1989.
[6]. I. Rechenberg, J.M. Zurada, R.J. Marks II, C. Goldberg, Evolution strategy, in computational intelligence: Imitating life, in: Computational Intelligence Imitating Life, IEEE Press, Piscataway, 1994.
[7]. N.J. Radcliffe, P.D. Surry, "Formal Memetic Algorithms", in: AISB Workshop on Evolutionary Computing, Springer, pp. 1–16, 1994.
[8]. R.G. Reynolds, "An introduction to cultural algorithms", in: Proceedings of the Third Annual Conference on Evolutionary Programming, World Scientific, pp. 131–139,1994.
[9]. S. Kirkpatrick, C.D. Gelatt, M.P. Vecchi, "Optimization by simulated annealing", Science, Vol. 220 , No. 4598, pp. 671–680, 1983.
[10]. R. Storn, K. Price, "Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces", J. Global Optim. Vol. 11, No.4, pp. 341–359, 1997.
[11]. X. Yao, Y. Liu, G. Lin, "Evolutionary programming made faster", IEEE Trans. Evol. Comput. Vol. 3 , No. 2, pp. 82–102, 1999.
[12]. Y.K. Kim, J.Y. Kim, Y. Kim, "A coevolutionary algorithm for balancing and sequencing in mixed model assembly lines", Appl. Intell. Vol. 13 , No. 3, pp. 247–258, 2000.
[13]. A. Sinha, D.E. Goldberg, "A Survey of Hybrid Genetic and Evolutionary Algorithms", IlliGAL report, Vol. 2003004, 2003.
[14]. E. Atashpaz-Gargari, C. Lucas, "Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition", in: 2007 IEEE Congress on Evolutionary Computation, IEEE, pp. 4661–4667, 2007.
[15]. D. Simon, "Biogeography-based optimization", IEEE Trans. Evol. Comput. Vol. 12 , No. 6, pp. 702–713, 2008.
[16]. E. Cuevas, A. Echavarría, M.A. Ramírez-Ortegón, "An optimization algorithm inspired by the states of matter that improves the balance between exploration and exploitation", Appl. Intell. Vol. 40, No. 2 , pp. 256–272, 2014.
[17]. S. Mirjalili, "SCA: A sine cosine algorithm for solving optimization problems", Knowl.-Based Syst., Vol. 96, pp. 120–133, 2016.
[18]. F. MiarNaeimi, G. Azizyan, M. Rashki, "Multi-level cross entropy optimizer (MCEO): An evolutionary optimization algorithm for engineering problems", Eng. Comput., Vol. 34 , No. 4, 2018.
[19]. H. Du, X. Wu, J. Zhuang, "Small-world optimization algorithm for function optimization", in: International Conference on Natural Computation, Springer, pp. 264–273, 2006.
[20]. R.A. Formato, "Central force optimization: A new metaheuristic with applications in applied electromagnetics", in: Progress in Electromagnetics Research, PIER 77, pp. 425–491,2007.
[21]. M.H. Tayarani-N, M.R. Akbarzadeh-T, "Magnetic optimization algorithms a new synthesis", in: 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), pp. 2659–2664, 2008.
[22]. E. Rashedi, H. Nezamabadi-Pour, S. Saryazdi, "GSA: A gravitational search algorithm", Inf. Sci., Vol. 179, No. 13, pp. 2232–2248, 2009.
[23]. A. Kaveh, S. Talatahari, "A novel heuristic optimization method: Charged system search", Acta Mech. Vol. 213, pp. 267–289, 2010.
[24]. A.Y.S. Lam, V.O.K. Li, "Chemical-reaction-inspired metaheuristic for optimization", IEEE Trans. Evol. Comput., Vol. 14, No 3, pp. 381–399, 2010.
[25]. A. Hatamlou, "Black hole: A new heuristic optimization approach for data clustering", Inf. Sci., Vol. 222 , pp. 175–184, 2013.
[26]. F.F. Moghaddam, R.F. Moghaddam, M. Cheriet, "Curved space optimization: A random search based on general relativity theory", arXiv, Vol. 1208, No. 2214, 2012.
[27]. A. Kaveh, T. Bakhshpoori, "Water evaporation optimization: A novel physically inspired optimization algorithm", Comput. Struct., Vol. 167, pp. 69–85, 2016.
[28]. H. Varaee, M.R. Ghasemi, "Engineering optimization based on ideal gas molecular movement algorithm", Eng. Comput. Vol. 33 , No. 1, pp. 71–93, 2017.
[29]. S. Mirjalili, S.M. Mirjalili, A. Hatamlou, "Multi-verse optimizer: A natureinspired algorithm for global optimization", Neural Comput. Appl., Vol. 27 , No. 2, pp. 495–513, 2016.
[30]. A. Kaveh, M.I. Ghazaan, "A new meta-heuristic algorithm: Vibrating particles system", Sci. Iran. Trans. A Civ. Eng., Vol. 24, No 2, pp. 551-566, 2017.
[31]. R. Eberhart, J. Kennedy, "A new optimizer using particle swarm theory", in: MHS’95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, IEEE, pp. 39–43, 1995.
[32]. S. Saremi, S. Mirjalili, A. Lewis, "Grasshopper optimisation algorithm: Theory and application", Adv. Eng. Softw., Vol. 105, pp. 30–47, 2017.
[33]. S. Mirjalili, "Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm", Knowl.-Based Syst., Vol. 89, pp.228–249, 2015.
[34]. X.L. Li, "A New Intelligent Optimization-Artificial Fish Swarm Algorithm", (Doctor thesis), Zhejiang University of Zhejiang, China, 2003.
[35]. D. Karaboga, "An Idea Based on Honey Bee Swarm for Numerical Optimization", Technical report-tr06, Erciyes university, engineering faculty, computer., 2005.
[36]. M. Roth, "Termite: A swarm intelligent routing algorithm for mobile wireless ad-hoc networks", Presented to the Faculty of the Graduate School of Cornell University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy, 2005.
[37]. M. Dorigo, M. Birattari, T. Stutzle, "Ant colony optimization", IEEE Comput. Intell. Mag. Vol. 1, No. 4, pp. 28–39, 2006.
[38]. M. Eusuff, K. Lansey, F. Pasha, "Shuffled frog-leaping algorithm: A memetic meta-heuristic for discrete optimization", Eng. Optim., Vol. 38, No. 2, pp. 129–154, 2006.
[39]. A. Mucherino, O. Seref, "Monkey search: A novel metaheuristic search for global optimization", in: AIP Conference Proceedings, American Institute of Physics, pp. 162–173, 2007.
[40]. Y. Shiqin, J. Jianjun, Y. Guangxing, "A dolphin partner optimization", in: Intelligent Systems, GCIS’09. WRI Global Congress On, IEEE, pp. 124–128, 2009.
[41]. X.S. Yang, "Firefly algorithm, stochastic test functions and design optimisation", arXiv, Vol. 1003, No. 1409, 2010.
[42]. X.S. Yang, "A new metaheuristic bat-inspired algorithm", in: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), Springer, pp. 65–74, 2010.
[43]. A. Askarzadeh, A. Rezazadeh, "A new heuristic optimization algorithm for modeling of proton exchange membrane fuel cell: Bird mating optimizer", Int. J. Energy Res., Vol. 37, No. 10, pp.1196–1204, 2013.
[44]. W.T. Pan, "A new fruit fly optimization algorithm: Taking the financial distress model as an example", Knowl.-Based Syst., Vol. 26, pp. 69–74, 2012.
[45]. B. Wang, X. Jin, B. Cheng, "Lion pride optimizer: An optimization algorithm inspired by lion pride behavior", Sci. China Inf. Sci., Vol. 55, No. 10, pp. 2369–2389, 2012.
[46]. A.H. Gandomi, A.H. Alavi, "Krill herd: A new bio-inspired optimization algorithm", Commun. Nonlinear Sci., Vol. 17 , No. 12, pp. 4831–4845, 2012.
[47]. S. Mirjalili, S.M. Mirjalili, A. Lewis, "Grey wolf optimizer", Adv. Eng. Softw., Vol. 69 , pp. 46–61, 2014.
[48]. A.H. Gandomi, X.S. Yang, A.H. Alavi, "Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems", Eng. Comput., Vol. 29, No. 1, pp. 17–35, 2013.
[49]. S. Mirjalili, "Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems", Neural Comput. Appl., Vol. 27, No. 4 , pp. 1053–1073, 2016.
[50]. S. Mirjalili, "A. Lewis, The whale optimization algorithm", Adv. Eng. Softw., Vol. 95, pp. 51–67, 2016.
[51]. S. Mirjalili, A.H. Gandomi, S.Z. Mirjalili, S. Saremi, H. Faris, S.M. Mirjalili, "Salp swarm algorithm: A bio-inspired optimizer for engineering design problems", Adv. Eng. Softw., Vol. 114, pp.163–191, 2017.
[52]. A.A. Heidari, S. Mirjalili, H. Faris, I. Aljarah, M. Mafarja, H. Chen, "Harris hawks optimization: Algorithm and applications", Future Gener. Comput. Syst., Vol. 97 pp. 849–872, 2019.
[53]. G. Azizyan, F. Miarnaeimi, M. Rashki, N. Shabakhty, "Flying squirrel optimizer (FSO): A novel SI-based optimization algorithm for engineering problems", Iran. J. Optim., Vol. 11, No. 2, pp.177–205, 2019.
[54]. N. Moosavian, B.K. Roodsari, "Soccer league competition algorithm: A novel meta-heuristic algorithm for optimal design of water distribution networks", Swarm Evol. Comput., Vol. 17, pp. 14–24, 2014.
[55]. J. Palmer, G. Sagar, "Agropyron repens (L.) Beauv. (Triticum repens L.; Elytrigia repens (L.) Nevski)", J. Ecol., Vol. 51, pp. 783–794, 1963.
[56]. P.A. Werner, R. Rioux, "The biology of Canadian weeds. 24. Agropyron repens (L.) Beauv. Can." J. Plant Sci., Vol. 57, pp. 905–919, 1977.
[57]. L.G. Holm, D.L. Plucknett., J.V. Pancho, J.P. Herberger, The World’s Worst Weeds, University Press: Honolulu, HI, USA, 1977.
[58]. C. Andreasen, I.M. Skovgaard, "Crop and soil factors of importance for the distribution of plant species on arable fields in Denmark", Agric. Ecosyst. Environ., Vol. 133, pp. 61–67, 2009.
[59]. J. Salonen, T. Hyvönen, H.A. Jalli, "Composition of weed flora in spring cereals in Finland—A fourth survey", Agric. Food Sci., Vol. 20, 2011.
[60]. P. A. Werneri , R. Rioux, "The Biology of Canadian Weeds. 24. Agropyron Repens (L.) Beauv", Canadian Journal of Plant Science, Vol. 57, pp. 905-919.
[61]. K.M. Ibrahim, P.M. Peterson, Grasses of Washington, D.C., Published by Smithsonian Institution Scholarly Press, Washington D.C., 2014.
[62]. X. Yao, Y. Liu, G. Lin, "Evolutionary Programming Made Faster", IEEE Transactions on Evolutionary Computation, Vol. 3, No. 2, pp. 82-102, 1999.
[63]. E. Rashedi, H. Nezamabadi-pour, S. Saryazdi, " GSA: A Gravitational Search Algorithm", Information Sciences, Vol. 179, pp. 2232–2248, 2009.
[64]. X. Yang, " Firefly algorithms for multimodal optimization", International conference on stochastic algorithms foundations and applications, pp.169–178, 2009.
[65]. Y. Li, Y. Zhao, Y. Shang, J. Liu " An improved firefly algorithm with dynamic self-adaptive adjustment", PLoS ONE, Vol. 16 ,2021.
[66]. D. Wang, D. Tan, L. Liu, " Particle swarm optimization algorithm: an overview", Soft Comput., Vol. 22, pp. 387–408 , 2018.
[1]. S.A. Mirjalili, "The Ant Lion Optimizer", Advances in Engineering Software , Vol. 83 , pp. 80–98, 2015.
[2]. F. MiarNaeimi, G.R. Azizyan, M. Rashki, "Horse herd optimization algorithm: A nature-inspired algorithm for high-dimensional optimization problems", Knowledge-Based Systems, Vol. 213, pp. 1-17, 2021.
[3]. J.H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, MIT press, 1992.
[4]. J.R. Koza, Genetic Programming: On the Programming of Computers By Means of Natural Selection, MIT press, 1992.
[5]. F. Glover, "Tabu search—Part I" , ORSA J. Comput. Vol. 1, No. 3, pp.190–206, 1989.
[6]. I. Rechenberg, J.M. Zurada, R.J. Marks II, C. Goldberg, Evolution strategy, in computational intelligence: Imitating life, in: Computational Intelligence Imitating Life, IEEE Press, Piscataway, 1994.
[7]. N.J. Radcliffe, P.D. Surry, "Formal Memetic Algorithms", in: AISB Workshop on Evolutionary Computing, Springer, pp. 1–16, 1994.
[8]. R.G. Reynolds, "An introduction to cultural algorithms", in: Proceedings of the Third Annual Conference on Evolutionary Programming, World Scientific, pp. 131–139,1994.
[9]. S. Kirkpatrick, C.D. Gelatt, M.P. Vecchi, "Optimization by simulated annealing", Science, Vol. 220 , No. 4598, pp. 671–680, 1983.
[10]. R. Storn, K. Price, "Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces", J. Global Optim. Vol. 11, No.4, pp. 341–359, 1997.
[11]. X. Yao, Y. Liu, G. Lin, "Evolutionary programming made faster", IEEE Trans. Evol. Comput. Vol. 3 , No. 2, pp. 82–102, 1999.
[12]. Y.K. Kim, J.Y. Kim, Y. Kim, "A coevolutionary algorithm for balancing and sequencing in mixed model assembly lines", Appl. Intell. Vol. 13 , No. 3, pp. 247–258, 2000.
[13]. A. Sinha, D.E. Goldberg, "A Survey of Hybrid Genetic and Evolutionary Algorithms", IlliGAL report, Vol. 2003004, 2003.
[14]. E. Atashpaz-Gargari, C. Lucas, "Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition", in: 2007 IEEE Congress on Evolutionary Computation, IEEE, pp. 4661–4667, 2007.
[15]. D. Simon, "Biogeography-based optimization", IEEE Trans. Evol. Comput. Vol. 12 , No. 6, pp. 702–713, 2008.
[16]. E. Cuevas, A. Echavarría, M.A. Ramírez-Ortegón, "An optimization algorithm inspired by the states of matter that improves the balance between exploration and exploitation", Appl. Intell. Vol. 40, No. 2 , pp. 256–272, 2014.
[17]. S. Mirjalili, "SCA: A sine cosine algorithm for solving optimization problems", Knowl.-Based Syst., Vol. 96, pp. 120–133, 2016.
[18]. F. MiarNaeimi, G. Azizyan, M. Rashki, "Multi-level cross entropy optimizer (MCEO): An evolutionary optimization algorithm for engineering problems", Eng. Comput., Vol. 34 , No. 4, 2018.
[19]. H. Du, X. Wu, J. Zhuang, "Small-world optimization algorithm for function optimization", in: International Conference on Natural Computation, Springer, pp. 264–273, 2006.
[20]. R.A. Formato, "Central force optimization: A new metaheuristic with applications in applied electromagnetics", in: Progress in Electromagnetics Research, PIER 77, pp. 425–491,2007.
[21]. M.H. Tayarani-N, M.R. Akbarzadeh-T, "Magnetic optimization algorithms a new synthesis", in: 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), pp. 2659–2664, 2008.
[22]. E. Rashedi, H. Nezamabadi-Pour, S. Saryazdi, "GSA: A gravitational search algorithm", Inf. Sci., Vol. 179, No. 13, pp. 2232–2248, 2009.
[23]. A. Kaveh, S. Talatahari, "A novel heuristic optimization method: Charged system search", Acta Mech. Vol. 213, pp. 267–289, 2010.
[24]. A.Y.S. Lam, V.O.K. Li, "Chemical-reaction-inspired metaheuristic for optimization", IEEE Trans. Evol. Comput., Vol. 14, No 3, pp. 381–399, 2010.
[25]. A. Hatamlou, "Black hole: A new heuristic optimization approach for data clustering", Inf. Sci., Vol. 222 , pp. 175–184, 2013.
[26]. F.F. Moghaddam, R.F. Moghaddam, M. Cheriet, "Curved space optimization: A random search based on general relativity theory", arXiv, Vol. 1208, No. 2214, 2012.
[27]. A. Kaveh, T. Bakhshpoori, "Water evaporation optimization: A novel physically inspired optimization algorithm", Comput. Struct., Vol. 167, pp. 69–85, 2016.
[28]. H. Varaee, M.R. Ghasemi, "Engineering optimization based on ideal gas molecular movement algorithm", Eng. Comput. Vol. 33 , No. 1, pp. 71–93, 2017.
[29]. S. Mirjalili, S.M. Mirjalili, A. Hatamlou, "Multi-verse optimizer: A natureinspired algorithm for global optimization", Neural Comput. Appl., Vol. 27 , No. 2, pp. 495–513, 2016.
[30]. A. Kaveh, M.I. Ghazaan, "A new meta-heuristic algorithm: Vibrating particles system", Sci. Iran. Trans. A Civ. Eng., Vol. 24, No 2, pp. 551-566, 2017.
[31]. R. Eberhart, J. Kennedy, "A new optimizer using particle swarm theory", in: MHS’95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, IEEE, pp. 39–43, 1995.
[32]. S. Saremi, S. Mirjalili, A. Lewis, "Grasshopper optimisation algorithm: Theory and application", Adv. Eng. Softw., Vol. 105, pp. 30–47, 2017.
[33]. S. Mirjalili, "Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm", Knowl.-Based Syst., Vol. 89, pp.228–249, 2015.
[34]. X.L. Li, "A New Intelligent Optimization-Artificial Fish Swarm Algorithm", (Doctor thesis), Zhejiang University of Zhejiang, China, 2003.
[35]. D. Karaboga, "An Idea Based on Honey Bee Swarm for Numerical Optimization", Technical report-tr06, Erciyes university, engineering faculty, computer., 2005.
[36]. M. Roth, "Termite: A swarm intelligent routing algorithm for mobile wireless ad-hoc networks", Presented to the Faculty of the Graduate School of Cornell University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy, 2005.
[37]. M. Dorigo, M. Birattari, T. Stutzle, "Ant colony optimization", IEEE Comput. Intell. Mag. Vol. 1, No. 4, pp. 28–39, 2006.
[38]. M. Eusuff, K. Lansey, F. Pasha, "Shuffled frog-leaping algorithm: A memetic meta-heuristic for discrete optimization", Eng. Optim., Vol. 38, No. 2, pp. 129–154, 2006.
[39]. A. Mucherino, O. Seref, "Monkey search: A novel metaheuristic search for global optimization", in: AIP Conference Proceedings, American Institute of Physics, pp. 162–173, 2007.
[40]. Y. Shiqin, J. Jianjun, Y. Guangxing, "A dolphin partner optimization", in: Intelligent Systems, GCIS’09. WRI Global Congress On, IEEE, pp. 124–128, 2009.
[41]. X.S. Yang, "Firefly algorithm, stochastic test functions and design optimisation", arXiv, Vol. 1003, No. 1409, 2010.
[42]. X.S. Yang, "A new metaheuristic bat-inspired algorithm", in: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), Springer, pp. 65–74, 2010.
[43]. A. Askarzadeh, A. Rezazadeh, "A new heuristic optimization algorithm for modeling of proton exchange membrane fuel cell: Bird mating optimizer", Int. J. Energy Res., Vol. 37, No. 10, pp.1196–1204, 2013.
[44]. W.T. Pan, "A new fruit fly optimization algorithm: Taking the financial distress model as an example", Knowl.-Based Syst., Vol. 26, pp. 69–74, 2012.
[45]. B. Wang, X. Jin, B. Cheng, "Lion pride optimizer: An optimization algorithm inspired by lion pride behavior", Sci. China Inf. Sci., Vol. 55, No. 10, pp. 2369–2389, 2012.
[46]. A.H. Gandomi, A.H. Alavi, "Krill herd: A new bio-inspired optimization algorithm", Commun. Nonlinear Sci., Vol. 17 , No. 12, pp. 4831–4845, 2012.
[47]. S. Mirjalili, S.M. Mirjalili, A. Lewis, "Grey wolf optimizer", Adv. Eng. Softw., Vol. 69 , pp. 46–61, 2014.
[48]. A.H. Gandomi, X.S. Yang, A.H. Alavi, "Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems", Eng. Comput., Vol. 29, No. 1, pp. 17–35, 2013.
[49]. S. Mirjalili, "Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems", Neural Comput. Appl., Vol. 27, No. 4 , pp. 1053–1073, 2016.
[50]. S. Mirjalili, "A. Lewis, The whale optimization algorithm", Adv. Eng. Softw., Vol. 95, pp. 51–67, 2016.
[51]. S. Mirjalili, A.H. Gandomi, S.Z. Mirjalili, S. Saremi, H. Faris, S.M. Mirjalili, "Salp swarm algorithm: A bio-inspired optimizer for engineering design problems", Adv. Eng. Softw., Vol. 114, pp.163–191, 2017.
[52]. A.A. Heidari, S. Mirjalili, H. Faris, I. Aljarah, M. Mafarja, H. Chen, "Harris hawks optimization: Algorithm and applications", Future Gener. Comput. Syst., Vol. 97 pp. 849–872, 2019.
[53]. G. Azizyan, F. Miarnaeimi, M. Rashki, N. Shabakhty, "Flying squirrel optimizer (FSO): A novel SI-based optimization algorithm for engineering problems", Iran. J. Optim., Vol. 11, No. 2, pp.177–205, 2019.
[54]. N. Moosavian, B.K. Roodsari, "Soccer league competition algorithm: A novel meta-heuristic algorithm for optimal design of water distribution networks", Swarm Evol. Comput., Vol. 17, pp. 14–24, 2014.
[55]. J. Palmer, G. Sagar, "Agropyron repens (L.) Beauv. (Triticum repens L.; Elytrigia repens (L.) Nevski)", J. Ecol., Vol. 51, pp. 783–794, 1963.
[56]. P.A. Werner, R. Rioux, "The biology of Canadian weeds. 24. Agropyron repens (L.) Beauv. Can." J. Plant Sci., Vol. 57, pp. 905–919, 1977.
[57]. L.G. Holm, D.L. Plucknett., J.V. Pancho, J.P. Herberger, The World’s Worst Weeds, University Press: Honolulu, HI, USA, 1977.
[58]. C. Andreasen, I.M. Skovgaard, "Crop and soil factors of importance for the distribution of plant species on arable fields in Denmark", Agric. Ecosyst. Environ., Vol. 133, pp. 61–67, 2009.
[59]. J. Salonen, T. Hyvönen, H.A. Jalli, "Composition of weed flora in spring cereals in Finland—A fourth survey", Agric. Food Sci., Vol. 20, 2011.
[60]. P. A. Werneri , R. Rioux, "The Biology of Canadian Weeds. 24. Agropyron Repens (L.) Beauv", Canadian Journal of Plant Science, Vol. 57, pp. 905-919.
[61]. K.M. Ibrahim, P.M. Peterson, Grasses of Washington, D.C., Published by Smithsonian Institution Scholarly Press, Washington D.C., 2014.
[62]. X. Yao, Y. Liu, G. Lin, "Evolutionary Programming Made Faster", IEEE Transactions on Evolutionary Computation, Vol. 3, No. 2, pp. 82-102, 1999.
[63]. E. Rashedi, H. Nezamabadi-pour, S. Saryazdi, " GSA: A Gravitational Search Algorithm", Information Sciences, Vol. 179, pp. 2232–2248, 2009.
[64]. X. Yang, " Firefly algorithms for multimodal optimization", International conference on stochastic algorithms foundations and applications, pp.169–178, 2009.
[65]. Y. Li, Y. Zhao, Y. Shang, J. Liu " An improved firefly algorithm with dynamic self-adaptive adjustment", PLoS ONE, Vol. 16 ,2021.
[66]. D. Wang, D. Tan, L. Liu, " Particle swarm optimization algorithm: an overview", Soft Comput., Vol. 22, pp. 387–408 , 2018.
