Binary bat algorithm

Seyedali Mirjalili1, Seyed Mohammad Mirjalili2, Xin-She Yang3
1School of Information and Communication Technology, Griffith University, Nathan, Brisbane, Australia
2Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, Shahid Beheshti University, Tehran, Iran
3Department of Engineering, University of Cambridge, Cambridge, UK

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Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, pp 1942–1948

Holland J (1975) Adaptation in natural and artificial systems. The University of Michigan Press, Ann Arbor, Michigan

Kirkpatrick S, Gelati CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671–680

Dorigo M, Maniezzo V, Colorni A (1996) The ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern B 26:29–41

Rashedi E, Nezamabadi S, Saryazdi S (2009) GSA: a gravitational search algorithm. Inf Sci 179:2232–2248

Kaveh A, Talatahari S (2010) A novel heuristic optimization method: charged system search. Acta Mech 213:267–289

Kaveh A, Share MAM, Moslehi M (2013) Magnetic charged system search: a new meta-heuristic algorithm for optimization. Acta Mech 224:85–107

Kaveh A, Khayatazad M (2012) A new meta-heuristic method: ray optimization. Comput Struct 112:283–294

Kaveh A, Farhoudi N (2013) A new optimization method: dolphin echolocation. Adv Eng Softw 59:53–70

Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evolut Comput 1:67–82

Yang XS (2010) A new metaheuristic bat-inspired algorithm. In: Gonzalez JR et al (eds) Nature inspired cooperative strategies for optimization (NICSO 2010), vol 284. Springer, Berlin, pp 65–74

Pal A, Maiti J (2010) Development of a hybrid methodology for dimensionality reduction in Mahalanobis–Taguchi system using Mahalanobis distance and binary particle swarm optimization. Expert Syst Appl 37:1286–1293

Babaoglu İ, Findik O, Ülker E (2010) A comparison of feature selection models utilizing binary particle swarm optimization and genetic algorithm in determining coronary artery disease using support vector machine. Expert Syst Appl 37:3177–3183

Qiao L-Y, Peng X-Y, Peng Y (2006) BPSO-SVM wrapper for feature subset selection. Dianzi Xuebao (Acta Electronica Sinica) 34:496–498

Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. J Simul 76:60–68

Storn R, Price K (1997) Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11:341–359

Tayarani-N MH, Akbarzadeh-T MR (2008) Magnetic optimization algorithms a new synthesis. In: IEEE congress on evolutionary computation, pp 2659–2664

Wang L, Xu Y, Mao Y, Fei M (2010) A discrete harmony search algorithm. In: Li K, Li X, Ma S, Irwin GW (eds) Life system modeling and intelligent computing. Communications in computer and information science, vol 98. Springer, Berlin, pp 37–43. http://dx.doi.org/10.1007/978-3-642-15859-9_6

Wang L, Fu X, Menhas MI, Fei M (2010) A modified binary differential evolution algorithm. In: Li K, Fei M, Jia L, Irwin GW (eds) Life system modeling and intelligent computing, Lecture notes in computer science, vol 6329. Springer, Berlin, pp 49–57. http://dx.doi.org/10.1007/978-3-642-15597-0_6

Mirjalili S, Mohd Hashim SZ (2011) BMOA: binary magnetic optimization algorithm. In: 2011 3rd international conference on machine learning and computing (ICMLC 2011), Singapore, 2011, pp 201–206

Rashedi E, Nezamabadi-pour H, Saryazdi S (2009) BGSA: binary gravitational search algorithm. Nat Comput 9:727–745

Kennedy J, Eberhart RC (1997) A discrete binary version of the particle swarm algorithm. In: IEEE international conference on computational cybernetics and simulation, pp 4104–4108

Tasgetiren MF, Suganthan PN, Pan QK (2007) A discrete particle swarm optimization algorithm for the generalized traveling salesman problem. In: 9th annual conference on genetic and evolutionary computation (GECCO ‘07), New York, NY, USA, 2007, pp 158–167

Mirjalili S, Lewis A (2013) S-shaped versus V-shaped transfer functions for binary particle swarm optimization. Swarm Evol Comput 9:1–14. http://dx.doi.org/10.1016/j.swevo.2012.09.002

Yao X, Liu Y, Lin G (1999) Evolutionary programming made faster. IEEE Trans Evolut Comput 3:82–102

Yang X-S (ed) (2010) Test problems in optimization. An introduction with metaheuristic applications. Wiley, London

Molga M, Smutnicki C (2005) Test functions for optimization needs. Available at http://www.zsd.ict.pwr.wroc.pl/files/docs/functions.pdf

Digalakis JG, Margaritis KG (2001) On benchmarking functions for genetic algorithms. Int J Comput Math 77:481–506

Liang JJ, Suganthan PN, Deb K (2005) Novel composition test functions for numerical global optimization. In: IEEE In swarm intelligence symposium pp 68–75

Derrac J, Molina GSD, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evolut Comput 1:3–18

Garcia S, Molina D, Lozano M, Herrera F (2009) A study on the use of non. J Heuristics 15:617–644

Wilcoxon F (1945) Individual comparisons by ranking methods. Biometrics 1:80–83

Okawachi Y, Foster MA, Sharping JE, Gaeta AL, Xu Q, Lipson M (2006) All-optical slow-light on a photonic chip. Opt Express 14:2317–2322

Freude W, Brosi J-M, Koos C, Vorreau P, Andreani L, Dumon P, Baets R, Esembeson B, Biaggio I, Michinobu T (2008) Silicon-organic hybrid (SOH) devices for nonlinear optical signal processing. In: Transparent optical networks 2008. ICTON 2008. 10th anniversary international conference on, 2008, pp 84–87

Tucker RS, Ku P-C, Chang-Hasnain CJ (2005) Slow-light optical buffers: capabilities and fundamental limitations. J Lightwave Technol 23:4046

Long F, Tian H, Ji Y (2010) A study of dynamic modulation and buffer capability in low dispersion photonic crystal waveguides. J Lightwave Technol 28:1139–1143

Mirjalili SM, Mirjalili S (2012) Light property and optical buffer performance enhancement using particle swarm optimization in oblique ring-shape-hole photonic crystal waveguide. Photon Glob Conf (PGC) 2012:1–4. doi: 10.1109/PGC.2012.6457997

Dai L, Jiang C (2009) Photonic crystal slow light waveguides with large delay-bandwidth product. Appl Phys B 95:105–111

Hou J, Gao D, Wu H, Hao R, Zhou Z (2009) Flat band slow light in symmetric line defect photonic crystal waveguides. Photon Technol Lett IEEE 21:1571–1573

Kurt H, Üstün K, Ayas L (2010) Study of different spectral regions and delay bandwidth relation in slow light photonic crystal waveguides. Opt Express 18:26965–26977

Zhai Y, Tian H, Ji Y (2011) Slow light property improvement and optical buffer capability in ring-shape-hole photonic crystal waveguide. Lightwave Technol J 29:3083–3090

Guo S, Albin S (2003) Simple plane wave implementation for photonic crystal calculations. Opt Express 11:167–175

Säynätjoki A, Mulot M, Ahopelto J, Lipsanen H (2007) Dispersion engineering of photonic crystal waveguides with ring-shaped holes. Opt Express 15:8323–8328

Wang D, Zhang J, Yuan L, Lei J, Chen S, Han J, Hou S (2011) Slow light engineering in polyatomic photonic crystal waveguides based on square lattice. Opt Commun 284:5829–5832

Engelen R, Sugimoto Y, Watanabe Y, Korterik JP, Ikeda N, van Hulst NF, Asakawa K, Kuipers L (2006) The effect of higher order dispersion on slow light propagation in photonic crystal waveguides. In: Lasers and electro-optics, 2006 and 2006 quantum electronics and laser science conference. CLEO/QELS 2006. conference on, 2006, pp 1–2

Frandsen LH, Lavrinenko A, Fage-Pedersen J, Borel PI (2006) Photonic crystal waveguides with semi-slow light and tailored dispersion properties. Opt Express 14:9444–9450

Kuramochi E, Notomi M, Hughes S, Shinya A, Watanabe T, Ramunno L (2005) Disorder-induced scattering loss of line-defect waveguides in photonic crystal slabs. Phys Rev B 72:161318

Mirjalili SM, Abedi K, Mirjalili S (2013) Optical buffer performance enhancement using particle swarm optimization in ring-shape-hole photonic crystal waveguide. Opt - Int J Light Electron Opt 124:5989–5993. doi: 10.1016/j.ijleo.2013.04.114

Mirjalili SM, Mirjalili S, Lewis A, Abedi K (2013) A tri-objective particle swarm optimizer for designing line defect photonic crystal waveguides. Photonics Nanostructures-Fundam Appl. doi: 10.1016/j.photonics.2013.11.001

Mirjalili SM, Mirjalili S, Lewis A (2013) A novel multi-objective optimization framework for designing photonic crystal waveguides. IEEE Photonics Technol Lett 99:1041–1135. doi: 10.1109/LPT.2013.2290318