یک الگوریتم الهام‌گرفته از طبیعت مبتنی بر نظریه شرطی‌سازی کلاسیک

[1] R. Haupt and S. E. Haupt, “Practical Genetic Algorithms”, 2nd Edition, John Wiley & Sons Inc, 2004.

[2] H. Yapıcı and N. Çetinkaya, “An Improved Particle Swarm Optimization Algorithm Using Eagle Strategy for Power Loss Minimization”, Hindawi, Mathematical Problems in Engineering, doi.org/10.1155/2017/1063045, 2017.

[3] W. Sun and Y. Yuan, “Optimization Theory and Methods: Nonlinear Programming”, Springer Science Business Media, LLC Press, 2006.

[4] Classical conditioning, “The Gale encyclopedia of psychology”, Gale Group, p. 124, 2001.

[5] J. Holland, “Genetic algorithms and the optimal allocation of trials”.SIAM J. Comput. 2, 88-105, 1979.

[6] F. Ali and M. Tawhid, “A hybrid particle swarm optimization and genetic algorithm with population partitioning for large scale optimization problems”, Ain Shams Engineering Journal, doi.org/10.1016/j.asej.2016.07.008, 2016.

[7] J. Kennedy and R. Eberhar, “Particle Swarm Optimization”, Proceedings of the 4^th IEEE International Conference on Neural Networks, pp. 1942-1948, 1995.

[8] N F. Wan and L. Nolle, “Solving a multi-dimensional knapsack problem using hybrid particle”.23rd European Conference on Modelling and Simulation, 2008.

[9] K B. Deep, “A socio-cognitive particle swarm optimization for multi-dimensional”. First International Conference on Emerging Trends in Engineering and, 355–360, 2008.

[10] X. Shen, Y. Li, C. Chen, J. Yang, D. Zhang, “Greedy continuous particle swarm optimisation algorithm for the knapsack problems”. International Journal of Computer Applications in Technology 44 (2), 37–144, 2012.

[11] H S. Lopes and L S. Coelho, “Particle swarn optimization with fast local search for the blind traveling salesman problem”. International Conference on Hybrid Intelligent Systems, 245–250, 2005.

[12] D. Karaboga and B. Basturk, “A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm”. Journal of Global Optimization 39, 2007.

[13] A. Banharnsakun and B. Sirinaovakul, “T. Achalakul, Job shop scheduling with the best-so-far ABC”.Engineering Applications of Artificial Intelligence 25 (3), 583–593, 2012.

[14] D. Karaboga and B. Gorkemli, “A combinatorial artificial bee colony algorithm for traveling salesman problem”.International Symposium on Intelligent Systems and Applications, pp. 50–53, 2011.

[15] Z. Geem, J. Kim,  G. Loganathan, “A new heuristic optimization algorithm: Harmony search”.Simulation, 60, 2011.

[16] DT. Pham, A. Ghanbarzadeh, E. Koc, S. Otri, S. Rahim, M. Zaidi, “The bees algorithm”. Technical note, Cardiff University, UK: Manufacturing Engineering Center, 2005.

[17] D T. Pham, S. Otri, A. Afify, M. Mahmuddin, H. Al-Jabbouli, “Data clustering using the bees algorithm”. 40thCIRPInternational Seminar on Manufacturing Systems, 2007.

[18] D. Pham, E. Koc, J. Lee, J. Phrueksanant, “Using the bees algorithm to schedule jobs for a machine”. Proceedings of Eighth International Conference on Laser Metrology, 430–439, CMM and Machine, 2007.

[19] X. Miao, J. Chu, L. Zhang, J. Qiao, “An Evolutionary Neural Network Approach to Simple Prediction of Dam Deformation”, Journal of Information & Computational Science, 1315–1324, 2013.

[20] M. Cheng and L. Lien, “Hybrid artificial intelligencebased pba for benchmark functions and facility layout design optimization”.  Journal of Computing in Civil Engineering, 26, 612–624, 2012.

[21] W. Feng and Ch. Liu, “A Novel Particle Swarm Optimization Algorithm for Global Optimization”, Hindawi Publishing Corporation Computational Intelligence and Neuroscience Volume 2016, Article ID 9482073, 9 pages, 2016.

[22] X. S. Yang and S. Deb, “Cuckoo search via Levy flights”, in ´ Proc. NaBIC 2009, IEEE Publications, 210-214, Dec. 2009. 18 / Information Sciences XX 1–22 19, 2014.

[23] P. Civicioglu, “Transforming geocentric cartesian coordinates to geodeticcoordinates by using differential search algorithm”. Comput, Geosciuk, 229-247, 2012.

[24] A. Gandomi, “Bird mating optimizer: An optimization algorithm inspired by birdmating strategies”. Commun Nonlinear Sci, 1213-1228, 2014.

[25] A. Draa, S. Bouzoubia, I. Boukhalfa, “A sinusoidal differential evolution algorithmfor numerical optimization”, Appl. Soft Comput, 99–126, 2015.

[26] G. Sun, R. Zhao, Y. Lan, “Joint operations algorithm for large-scale global optimization”. Applied Soft Computing, 38: 1025-1039, 2016.

[27] X. Xu, Y. Tang, J. Li, CC. Hua, X P. Guan, “Dynamic multi-swarm particle swarmoptimizer with cooperative learning strategy”, Appl. Soft Comput. 29, 169–183, 2015.

[28] J. Wang, B. Zhou, Sh, Zhou, “An Improved Cuckoo Search Optimization Algorithm for the Problem of haotic Systems Parameter Estimation”, Hindawi Publishing Corporation, Computational Intelligence and Neuroscience, Volume 2016, 10.1155/2016/2959370, 2016.

[29] E R. Tanweer, S. Suresh, N. Sundararajan, “Self regulating particle swarm optimization algorithm”, Innovative Applications of Artificial Neural Networks in Engineering, Volume 294, 182–202, 2015.

[30] F T. Zhao, Zh. Yao, J. Luan, X. Son, “A Novel Fused Optimization Algorithm of Genetic Algorithm and Ant Colony Optimization”, athematical Problems in Engineering, Volume 2016 (2016), Article ID 2167413, 2016.

[31] M. Thankur, “A new genetic algorithm for global optimization of multimodal continuous functions”, Journal of Computational Science, 298–311, 2014.

[32] Q. Zhang, A.Zhou, Sh. Zhao, P. Suganthan, W. Liu, S. Tiwari, “Multiobjective optimization test instances for the CEC 2009 Special Session and Competition”, Technical Report CES-487, 2009.

[33] R. Storn and K. Price, “Differential evolution a simple and efficient heuristic for global optimization over continuous spaces”, Journal of Global Optimization, 11 (1997) 341–359, 1997.

[34] A. Gao and W B. Xu, “A new particle swarm algorithm and its globally convergent modifications”, IEEE Trans. Syst. Man. Cy. B, vol. 41, no. 5, 1334-1351, 2011.

[35] R. Mallipeddi, P N. Suganthan, Q. Pan, M. Tasgetiren, “Differential evolution algorithm with ensemble of parameters and mutation strategies”, Appl. Soft. Comput, 1679-1696, 2011.

[36] Y. Liang, Y. Liu,  L. Zhang, “An Improved Artificial Bee Colony (ABC) Algorithm for Large  Scale Optimization”, 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA), IEEE, 978-1-4799-2716-6/13/$31.00, 2013.

[37] X S. Yang, “Nature-Inspired Metaheuristic Algorithms: Second Edition”, Luniver Press, 2011.

[38] E. Rashedi, H. Nezamabadi-pour, S. Saryazdi, “GSA: A Gravitational Search Algorithm”, Inform. Sciences, 2232-2248, 2009.

[39] R M. Rizk Allah, “Hybridization of Fruit Fly Optimization Algorithm and Firefly Algorithm for Solving Nonlinear Programming Problems”, International Journal of Swarm Intelligence and  Evolutionary Computation, 2016.

[40] J. G. Villegas, “Using Nonparametric Test to Compare the Performance of Metaheuristics”, friedman-test-24062011.pdf, 2001.

[41] Statistical Consultant for Doctoral Students and Researchers, http://www.statisticallysignificantconsulting.com/Ttest.htm.

[42] م. امیرعباسیان، ح. نظام‌آبادی پور، «الگوریتم جستجوی گرانشی چندهدفه مبتنی بر مرتب‌سازی چبهه‌های مغلوب‌نشده»، مجله مهندسی برق دانشگاه تبریز، شماره 1 جلد 41، ص61-81‌، 1391.

[43] ش. جمالی، س. ملک تاجی، م. آنالویی، « مکان‌یابی ماشین‌های مجازی با استفاده از الگوریتم رقابت استعماری»، مجله مهندسی برق دانشگاه تبریز، شماره 1 جلد 46، ص75، 1395.

[44] م. محمدپور، ح. پروین، « الگوریتم ژنتیک آشوب‌گونه مبتنی بر حافظه و خوشه‌بندی برای حل مسائل بهینه‌سازی پویا»، مجله مهندسی برق دانشگاه تبریز، شماره 3 جلد 46، ص77، 1395.