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Artificial Intelligence Review

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13.07.2017

Continuous versions of firefly algorithm: a review

verfasst von: Surafel Luleseged Tilahun, Jean Medard T. Ngnotchouye, Nawaf N. Hamadneh

Erschienen in: Artificial Intelligence Review | Ausgabe 3/2019

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Abstract

Firefly algorithm is a swarm based metaheuristic algorithm designed for continuous optimization problems. It works by following better solutions and also with a random search mechanism. It has been successfully used in different problems arising in different disciplines and also modified for discrete problems. Unlike its easiness to understand and to implement; its effectiveness is highly affected by the parameter values. In addition modifying the search mechanism may give better performance. Hence different modified versions are introduced to overcome its limitations and increase its performance. In this paper, the modifications done on firefly algorithm for continuous optimization problems will be reviewed with a critical analysis. A detailed discussion on the modifications with possible future works will also be presented. In addition a comparative study will be conducted using forty benchmark problems with different dimensions based on ten base functions. The result shows that some of the modified versions produce superior results with a tradeoff of high computational time. Hence, this result will help practitioners to decide which modified version to apply based on the computational resource available and the sensitivity of the problem.

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Abdelaziz AY, Mekhamer SF, Badr MAL, Algabalawy MA (2015) The firefly meta-heuristic algorithms: developments and applications. Int Electr Eng J (IEEJ) 6(7):1945–1952

Abdel-Raouf O, Abdel-Baset M, El-henawy I (2014) Chaotic firefly algorithm for solving definite integral, I.J. information technology and computer. Science 06:19–24

Abshouri AA, Meybodi MR, Bakhtiary A (2011) New firefly algorithm based on multi swarm & learning Automata in dynamic environments. In: Third international conference on signal processing systems (ICSPS2011), August 27Ű28, Yantai, China, 73–77, IEEE

Ali N, Othman MA, Husain MN, Misran MH (2014) A review of firefly algorithm. ARPN J Eng Appl Sci 9(10):1732–1736

Al-Wagih K (2015) Improved firefly algorithm for unconstrained optimization problems. Int J Comput Appl Technol Res 4(1):77–81

Alweshah M (2014) Firefly algorithm with artificial neural network for time series problems. Res J Appl Sci Eng Technol 7(19):3978–3982CrossRef

Amaya I, Cruz J, Correa R (2014) A modified firefly-inspired algorithm for global computatiional optimization. DYNA 81(187):85–90CrossRef

Amiri B, Hossain L, Crawford JW, Wigand RT (2013) Community detection in complex networks: multi-objective enhanced firefly algorithm. Knowl Based Syst 46:1–11CrossRef

Ariyaratne MKA, Pemarathne WPJ (2015) A review of recent advancements of firefly algorithm: a modern nature inspired algorithm. In: Proceedings of the 8th international research conference, 61–66, KDU, Published November 2015

Arora S, Singh S (2014a) Performance research on firefly optimization algorithm with mutation. In: International conference on communication, computing & systems (ICCCS2014), 168–172

Arora S, Singh S, Singh S, Sharma B (2014b) Mutated fireïňĆy algorithm. In: International conference on parallel, distributed and grid computing, IEEE, 33–38

Azad SK (2011) Optimum design of structures using an improved firefly algorithm. Int J Opt Civil Eng 2:327–340

Baghlani A, Makiabadi MH, Rahnema H (2013) A new accelarated firefly algorithm for size optimization of truss structures. Scientia Iranica Trans A Civil Eng 20(6):1612–1625

Banati H, Bajaj M (2011) Fire fly based feature selection approach. IJCSI Int J Comput Sci Issues 8(4):473–480

Bidar M, Kanan HR (2013) Jumper firefly algorithm. In: Proceeding of international conference on computer and knowledge engineering (ICCKE 2013), Oct. 31–Nov. 01, 2013, Ferdowsi University of Mashhad, 278–282

Bingham D (2016) Virtual library of simulation experiments: test functions and datasets, 2015. http://www.sfu.ca/~ssurjano/michal.html. Accessed Feb 2016

Brajevic I, Ignjatovic J (2015) An enhanced firefly algorithm for mixed variable structural optimization problems. Ser Math Inf 30(4):401–417MathSciNetMATH

Cheung NJ, Ding X-M, Shen H-B (2014) Adaptive firefly algorithm: parameter analysis and its application. PLoS ONE 9(11):1–12

Coelho LdS, Mariani VC (2012) Firefly algorithm approach based on chaotic Tinkerbell map applied to multivariable PID controller tuning. Comput Math Appl 64:2371–2382MathSciNetMATHCrossRef

Coelho LdS, Mariani VC (2013) Improved firefly algorithm approach applied to chiller loading for energy conservation. Energy Build 59:273–278CrossRef

Coelho LdS, de A Bernert DL, Mariani VC (2011) A chaotic firefly algorithm applied to reliability-redundancy optimization. In: 2011 IEEE congress on evolutionary computation (CEC11), 517–521

de Paula LCM, Soares AS, Soares TWL, Delbem ACB, Coelho CJ, Filho ARG (2014) Parallelization of a modified firefly algorithm using GPU for variable selection in a multivariate calibration problem. Int J Nat Comput Res 4(1):31–42CrossRef

Dhal KG, Quraishi MdI, Das S (2015a) A chaotic levy flight approach in bat and firefly algorithm for gray level image enhancement. I.J. Image Gr Signal Process 7:69–76

Dhal KG, Quraishi MdI, Das S (2015b) Development of firefly algorithm via chaotic sequence and population diversity to enhance the image contrast. Nat Comput. doi:10.1007/s11047-015-9496-3

Dieterich J, Hartke B (2012) Empirical review of standard benchmark functions using evolutionary global optimization. Appl Math 3:1552–1564CrossRef

Dugonik J, Fister I (2014) Multi-population firefly algorithm. In: Proceedings of the 2014, 1st student computer science research conference, Ljubljana, Slovenia, 7 October 19–23

Farahani ShM, Abshouri AA, Nasiri B, Meybodi MR (2011a) An improved firefly algorithm with directed movement. In: Proceedings of 4th IEEE international conference on computer science and information technology, Chengdu, 248–251

Farahani ShM, Abshouri AA, Nasiri B, Meybodi MR (2011b) A Gaussian firefly algorithm. Int J Mach Learn Comput 1(5):448–453

Farahani SM, Nasiri B, Meybodi MR (2011c) A multiswarm basedfirefly algorithm in dynamic environments. In Third international conference on signal processing systems (ICSPS2011), August 27–28, Yantai, China, 68–72, IEEE

Fateen S-EK, Bonilla-Petriciolet A (2014) Intelligent firefly algorithm for global optimization. In: Yang X-S (ed) Cuckoo search and firefly algorithm, studies in computational intelligence 516, 315–330

Fister I, Yang X-S, Brest J, Fister I Jr (2013a) Modified firefly algorithm using quaternion representation. Expert Syst Appl 40:7220–7230

Fister I, Fister Jr I, Yang XS, Brest J (2013b) A comprehensive review of firefly algorithms, swarm and evolutionary computation. doi:10.1016/j.swevo.2013.06.001

Fister I, Yang X-S, Brest J, Fister Jr I (2014) On the randomized FireïňĆy Algorithm. In: Yang X-S (ed) Cuckoo search and FireïňĆy algorithm, studies in computational intelligence 516, 27–48

Fu Q, Liu Z, Tong N, Wang M, Zhao Y (2015) A novel firefly algorithm based on improved learning mechanism. In: International conference on logistics engineering, management and computer science (LEMCS 2015), 1343–1351

Gandomi AH, Yang X-S, Talatahari S, Alavi AH (2013) FireïňĆy algorithm with chaos. Commun Nonlinear Sci Numer Simulat 18:89–98MATHCrossRef

Gavana A (2013) Global optimization benchmarks and AMPGO. http://infinity77.net/global_optimization/test_functions_nd_X.html. Accessed Feb 2016

Goel S, Panchal VK (2014) Performance evaluation of a new modified firefly algorithm. In: 3rd International conference reliability, infocom technologies and optimization (ICRITO) (Trends and Future Directions), IEEE

Grachten M, Arcos JL, de Mantaras RL (2014) Evolutionary optimization of music performance annotation. In: CMMR, 1–12

Hamadneh N, Sathasivam S, Tilahun SL, Choon OH (2012) Learning logic programming in radial basis function network via genetic algorithm. J Appl Sci (Faisalabad) 12(9):840–847MATH

Hassanzadeh T, Kanan HR (2014) Fuzzy FA: a modified firefly algorithm. Appl Artif Intell 28:47–65CrossRef

Hernandez S, Fontan A (2014) Cost optimization in bridge construction: application to launched bridges. Struct Congr 2014:2801–2812

Hongwei Z, Liwei T, Dongzheng W (2015) Research on improved firefly optimization algorithm based on cooperative for clustering. Int J Smart Home 9(3):205–214CrossRef

Husselmann AV, Hawick KA (2011) Parallel parametric optimisation with firefly algorithms on graphical processing units, Technical Report CSTN-141

Jamil M, Yang X-S (2013) A literature survey of benchmark functions for global optimization problems. Int J Math Model Numer Optim 4(2):150–194MATH

Jansi S, Subashini P (2015) A novel fuzzy clustering based modified firefly algorithm with chaotic map for mri brain tissue segmentation. MAGNT Res Rep 3(1):52–58

Kanimozhi T, Latha K (2013) An adaptive approach for content based image retrieval using Gaussian firefly algorithm. In: Huang DS et al. (eds) ICIC 2013, CCIS 375, pp 213–218

Kavousi-Fard A, Samet H, Marzbani F (2014) A new hybrid modified firefly algorithm and support vector regression model for accurate short term load forecasting. Expert Syst Appl 41:6047–6056CrossRef

Kazemzadeh-Parsi MJ (2014) A modified firefly algorithm for engineering design optimization problems. IJST Trans Mech Eng 38(M2):403–421

Kazemzadeh-Parsi MJ (2015) Optimal shape design for heat conduction using smoothed fixed grid finite element method and modified firefly algorithm. IJST Trans Mech Eng 39(M2):367–387

Kazemzadeh-Parsi MJ, Daneshmand F, Ahmadfard MA, Adamowski J (2015) Optimal Remediation Design of Unconfined Contaminated Aquifers Based on the Finite Element Method and a Modified Firefly Algorithm. Water Resour Manage. doi:10.1007/s11269-015-0976-0

Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks IV, Nov 27–Dec 1, Perth, Australia, IEEE, 4, 1942–1948

Khan WA, Hamadneh NN, Tilahun SL, Ngnotchouye JMT (2016) A review and comparative study of firefly algorithm and its modified versions. In: Chapter 13 of optimization algorithms- methods and applications, associate Prof. Ozgur Baskan (Ed.), InTech, doi:10.5772/62472

Kwiecien J, Filipowicz B (2012) Firefly algorithm in optimization of queueing systems. Bull Pol Acad Sci Tech Sci 60(2):363–368

Lin X, Zhong Y, Zhang H (2013) An enhanced firefly algorithm for function optimisation problems. Int J Modell Identif Control 18(2):166–173CrossRef

Liu C, Zhao Y, Gao F, Liu L (2015) Three-dimensional path planning method for autonomous underwater vehicle based on modified firefly algorithm. Math Probl Eng 2015, Article ID 561394, 10 pages

Long NC, Meesad P, Unger H (2015) A highly accurate firefly based algorithm for heart disease prediction. Expert Syst Appl 42:8221–8231CrossRef

Lucia A, Xu J (1990) Chemical process optimization using Newton-like methods. Comput Chrm Eng 14(2):119–138CrossRef

Lukasik S, Zak S (2009) Firefly algorithm for continuous constrained optimization task, ICCCI 2009. In: Ngugen NT, Kowalczyk R, Chen SM (eds) Lecture notes in artificial intelligence, 5796, 97–100

Maidl G, Schwerz de Lucena D, dos S Coelho L (2013) Economic dispatch optimization of thermal units based on a modified firefly algorithm. In: 22nd International congress of mechanical engineering (COBEM 2013), November. ABCM, RibeirÃčo Preto, SP, Brazil, pp 3–7

Manoharan GV, Shanmugalakshmi R (2015) Multi-objective firefly algorithm for multi-class gene selection. Ind J Sci Technol 8(1):27–34CrossRef

Meena S, Chitra K (2015) Modified approach of firefly algorithm for non-minimum phase systems. Indian J Sci Technol 8(23):1–8CrossRef

Mohammadi S, Mozafari B, Solimani S, Niknam T (2013) An adaptive modified firefly optimisation algorithm based on Hong’s point estimate method to optimal operation management in a microgrid with consideration of uncertainties. Energy 51:339–348CrossRef

Molga M, Smutnicki C (2016) Test functions for optimization needs, 2005, Retrieved Feb 2016. http://www.bioinformaticslaboratory.nl/twikidata/pub/Education/NBICResearchSchool/Optimization/VanKampen/BackgroundInformation/TestFunctions-Optimization.pdf

Negnevitsky M (2005) Artifcial intelligence: a guide to intelligent system. Henry Ling Limited, Harlow

Olamaei J, Moradi M, Kaboodi T (2013) A new adaptive modified firefly algorithm to solve optimal capacitor placement problem. In: 18th Electric power disteibution network conference, art. No. 6565962

Ondrisek B (2009) E-voting system security optimization. In: Proceedings of the 42nd Hawaii international conference on system sciences, Jan. 2009, 1–8

Othman MM, Hegazy YG, Abdelaziz AY (2015) A modified firefly algorithm for optimal sizing and siting of voltage controlled distributed generators in distribution networks. Period Polytech Electr Eng Comput Sci 59(3):104–109CrossRef

Pan F, Ye C, Wang K, Jiangbo Cao (2013) Research on the vehicle routing problem with time windows using firefly algorithm. J Comput 8(9):2256–2261CrossRef

Pike J, Bogich T, Elwood S, Finnoff DC, Daszak P (2014) Economic optimization of a global strategy to address the pandemic threat. Proc Natl Acad Sci 111(52):18519–18523CrossRef

Poursalehi N, Zolfaghari A, Minuchehr A, Moghaddam HK (2013) Continuous firefly algorithm applied to PWR core pattern enhancement. Nucl Eng Des 258:107–115CrossRef

Reddy PDP, Sekhar JNC (2014) Application of firefly algorithm for combined economic load and emission dispatch. Int J Rec Innov Trends Comput Commun 2(8):2448–2452

Ropponen A, Ritala R, Pistikopoulos EN (2010) Broke management optimization in design of paper production systems. In: Computer aided chemical engineering (20th European symposium on computer aided process engineering), 28, 865–870

Sahoo A, Chandra S (2013) Levy-flight firefly algorithm based active contour model for medical image segmentation, Contemporary Computing (IC3). In: Sixth international conference, IEEE, 159–162

Selvarasu R, Kalavathi MS (2015) TCSC placement for loss minimization using self adaptive firefly algorithm. J Eng Sci Technol 10(3):291–306

Selvarasu R, Kalavathi MS, Rajan CCA (2013) SVC placement for voltage constrained loss minimization using self-adaptive Firefly algorithm. Arch Electr Eng 62(4):649–661CrossRef

Shafaati M, Mojallali H (2012) Modified firefly optimization for IIR system identification. Control Eng Appl Inf 14(4):59–69

Shakarami MR, Sedaghati R (2014) A new approach for network reconfiguration problem in order to deviation bus voltage minimization with regard to probabilistic load model and DGs. Int J Electr Comput Energ Electr Commun Eng 8(2):430–435

Subotic M, Tuba M, Stanarevic N (2012) Parallelization of the firefly algorithm for unconstrained optimization problems. Latest Adv Inf Sci Appl 264–269, ISBN: 978-1-61804-092-3

Subramanian R, Thanushkodi K (2013) An efficient firefly algorithm to solve economic dispatch problems. Int J Soft Comput Eng (IJSCE) 2(1):52–55

Sulaiman MH, Daniyal H, Mustafa MW (2012) Modified firefly algorithm in solving economic dispatch problems with practical constraints. In: IEEE international conference on power and energy (PECon), 2–5 December 2012, Kota Kinabalu Sabah, Malaysia

Sweitzer BJ (2008) Preoperative screening, evaluation, and optimization of the patient’s medical status before outpatient surgery. Curr Opin Anaesthesiol 21(6):711–718CrossRef

Tian Y, Gao W, Yan S (2012) An improved inertia weight firefly optimization algorithm and application. In: 2012 International conference on control engineering and communication technology. IEEE 64–68

Tilahun SL, Asfaw A (2012) Modeling the expansion of Prosopis Juliflora and determining its optimum utilization rate to control its invasion in afar regional state of ethiopia. Int J Appl Math Res 1(4):726–743CrossRef

Tilahun SL, Ngnotchouye JMT (2016) Prey predator algorithm with adaptive step length. Int J Bio-Inspir Comput 8(4):195–204CrossRef

Tilahun SL, Ngnotchouye JMT (2017) Firefly algorithm for discrete optimization problems: a survey. KSCE J Civil Eng 21(2):535–545CrossRef

Tilahun SL, Ong HC (2012a) Bus timetabling as a fuzzy multiobjective optimization problem using preference based genetic algorithm. PROMET—traffic & transportation 24(3):183–191

Tilahun SL, Ong HC (2012b) Fuzzy preference of multiple decision makers in solving multiobjective optimization problems using genetic algorithm. Maejo Int J Sci Technol 6(02):224–237

Tilahun SL, Ong HC (2012c) Modified firefly algorithm. J Appl Math, Article ID 467631, 12 pages

Tilahun SL, Ong HC (2013) Vector optimisation using fuzzy preference in evolutionary strategy based firefly algorithm. Int J Op Res 16(1):81–95MathSciNetMATHCrossRef

Tilahun SL, Ong HC (2014) Prey-predator algorithm: a new metaheuristic optimization algorithm. Int J Inf Technol Decis Mak 13:1–22CrossRef

Tilahun SL, Kassa SM, Ong HC (2012) A new algorithm for multilevel optimization problems using evolutionary strategy, inspired by natural adaptation. In: Anthony A, Ishizuka M, Lukose D (eds) PRICAI 2012, LNAI 7458. Springer, Berlin, pp 577–588

Tilahun SL, Hamadneh NN, Sathasivam S, Ong HC (2013) Prey-predator algorithm as a new optimization technique using in radial basis function neural networks. Res J Appl Sci 8(7):383–387

Tilahun SL, Ong HC, Ngnotchouye JM (2016) Extended prey predator algorithm with a group hunting scenario. Advances in Operations Research. doi:10.1155/2015/587103

Tilahun SL (2017) Prey predator hyperheuristic. Appl. Soft Comput 59:104–114CrossRef

Verma OP, Aggarwal D, Patodi T (2016) Opposition and dimensional based modiïňĄed firefly algorithm. Expert Syst Appl 44:168–176CrossRef

Villegas JG (2016) Using nonparametric test to compare the performance of metaheuristics. https://juangvillegas.les.wordpress.com/2011/08/friedman-test24062011.pdf. Retrieved Feb 2016

Volpato G, Maria E, Michielin Z, Ferreira SRS, Petrus JCC (2008) Optimization of the chicken breast cooking process. J Food Eng 84(4):576–581CrossRef

Wadhwa Y, Kaur P, Kaur B (2014) Golomb Ruler sequence generation and optimization using modified firefly algorithm. SSRG Int J Electr Commun Eng (SSRG-IJECE) 1(5):1–8

Wang G, Guo L, Duan H, Liu L, Wang H (2012) A modified firefly algorithm for UCAV path planning. Int J Hybrid Inf Technol 5(3):123–144

Wang G-G, Guo L, Duan H, Wang H (2014a) A new improved FireïňĆy algorithm for global numerical optimization. J Comput Theor Nanosci 11:477–485

Wang B, Li D-X, Jiang J-P, Liao Y-H (2014b) A modified firefly algorithm based on light intensity difference. J Comb Optim. 31:1045–1060. doi:10.1007/s10878-014-9809-y

Yan X, Zhu Y, Wu J, Chen H (2012) An improved FireïňĆy algorithm with adaptive strategies. Adv Sci Lett 16:249–254CrossRef

Yang X-S (2008) Nature-inspired metaheuristic algorithm, 2nd edn. Luniver Press, England

Yang XS (2010) Firefly algorithm, levy flights and global optimization. In: Bramer M, Ellis R, Petridis M (eds) Research and development in intelligent systems XXVI. Springer, London, pp 209–218CrossRef

Yang X-S (2011) Review of metaheuristics and generalized evolutionary walk algorithm. Int J Bio-Inspir Comput 3(2):77–84CrossRef

Yang X-S (2013) Multiobjective ïňĄreïňĆy algorithm for continuous optimization. Eng Comput 29:175–184CrossRef

Yu S, Yang S, Su S (2013) Self-adaptive step firefly algorithm. J Appl Math 832718:8MathSciNetMATH

Yu S, Zhu S, Ma Y, Mao D (2015a) A variable step size ïňĄreïňĆy algorithm for numerical optimization. Appl Math Comput 263:214–220

Yu S, Mao D, Zhu S, Ma Y (2015b) Enhancing firefly algorithm using generalized opposition-based learning. Computing 97:741–754

Yu S, Su S, Huang L (2015) A simple diversity guided firefly algorithm. Kybernetes 44(1):43–56CrossRef

Titel: Continuous versions of firefly algorithm: a review
verfasst von: Surafel Luleseged Tilahun
Jean Medard T. Ngnotchouye
Nawaf N. Hamadneh
Publikationsdatum: 13.07.2017
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 3/2019
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-017-9568-0

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