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2016 | OriginalPaper | Chapter

12. Bee Metaheuristics

Authors : Ke-Lin Du, M. N. S. Swamy

Published in: Search and Optimization by Metaheuristics

Publisher: Springer International Publishing

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Abstract

This chapter introduces various algorithms that are inspired by the foraging, mating, fertilization, and communication behaviors of honey bees. Artificial bee colony (ABC) algorithm and marriage in honeybees optimization are described in detail.

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Literature
1.
go back to reference Abbass HA. MBO: Marriage in honey bees optimization—a haplometrosis polygynous swarming approach. In: Proceedings of the IEEE congress on evolutionary computation (CEC2001), Seoul, Korea, May 2001. p. 207–214. Abbass HA. MBO: Marriage in honey bees optimization—a haplometrosis polygynous swarming approach. In: Proceedings of the IEEE congress on evolutionary computation (CEC2001), Seoul, Korea, May 2001. p. 207–214.
2.
go back to reference Afshar A, Bozog Haddad O, Marino MA, Adams BJ. Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation. J Frankl Inst. 2007;344:452–462. Afshar A, Bozog Haddad O, Marino MA, Adams BJ. Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation. J Frankl Inst. 2007;344:452–462.
3.
go back to reference Akay B, Karaboga D. Parameter tuning for the artificial bee colony algorithm. In:Proceedings of the 1st international conference on computational collective intelligence (ICCCI): Semantic web, social networks and multiagent systems, Wroclaw, Poland, October 2009. p. 608–619. Akay B, Karaboga D. Parameter tuning for the artificial bee colony algorithm. In:Proceedings of the 1st international conference on computational collective intelligence (ICCCI): Semantic web, social networks and multiagent systems, Wroclaw, Poland, October 2009. p. 608–619.
4.
go back to reference Akay B, Karaboga D. A modified artificial bee colony algorithm for real-parameter optimization. Inf Sci. 2012;192:120–42.CrossRef Akay B, Karaboga D. A modified artificial bee colony algorithm for real-parameter optimization. Inf Sci. 2012;192:120–42.CrossRef
5.
go back to reference Akbari R, Mohammadi A, Ziarati K. A novel bee swarm optimization algorithm for numerical function optimization. Commun Nonlinear Sci Numer Simul. 2010;15:3142–55.MathSciNetCrossRefMATH Akbari R, Mohammadi A, Ziarati K. A novel bee swarm optimization algorithm for numerical function optimization. Commun Nonlinear Sci Numer Simul. 2010;15:3142–55.MathSciNetCrossRefMATH
6.
go back to reference Alam MS, Ul Kabir MW, Islam MM. Self-adaptation of mutation step size in artificial bee colony algorithm for continuous function optimization. In: Proceedings of the 13th international conference on computer and information technology (ICCIT), Dhaka, Bangladesh, December 2010. p. 69–74. Alam MS, Ul Kabir MW, Islam MM. Self-adaptation of mutation step size in artificial bee colony algorithm for continuous function optimization. In: Proceedings of the 13th international conference on computer and information technology (ICCIT), Dhaka, Bangladesh, December 2010. p. 69–74.
7.
go back to reference Alfonso W, Munoz M, Lopez J, Caicedo E. Optimización de funciones inspirada en el comportamiento de búsqueda de néctar en abejas. In: Congreso Internacional de Inteligenicia Computacional (CIIC2007), Bogota, Colombia, September 2007. Alfonso W, Munoz M, Lopez J, Caicedo E. Optimización de funciones inspirada en el comportamiento de búsqueda de néctar en abejas. In: Congreso Internacional de Inteligenicia Computacional (CIIC2007), Bogota, Colombia, September 2007.
8.
go back to reference Awadallah MA, Bolaji AL, Al-Betar MA. A hybrid artificial bee colony for a nurse rostering problem. Appl Soft Comput. 2015;35:726–39.CrossRef Awadallah MA, Bolaji AL, Al-Betar MA. A hybrid artificial bee colony for a nurse rostering problem. Appl Soft Comput. 2015;35:726–39.CrossRef
9.
go back to reference Babaoglu I. Artificial bee colony algorithm with distribution-based update rule. Appl Soft Comput. 2015;34:851–61.CrossRef Babaoglu I. Artificial bee colony algorithm with distribution-based update rule. Appl Soft Comput. 2015;34:851–61.CrossRef
10.
go back to reference Banharnsakun A, Achalakul T, Sirinaovakul B. The best-so-far selection in artificial bee colony algorithm. Appl Soft Comput. 2011;11(2):2888–901.CrossRef Banharnsakun A, Achalakul T, Sirinaovakul B. The best-so-far selection in artificial bee colony algorithm. Appl Soft Comput. 2011;11(2):2888–901.CrossRef
11.
go back to reference Bilal A. Chaotic bee colony algorithms for global numerical optimization. Expert Syst Appl. 2010;37:5682–7.CrossRef Bilal A. Chaotic bee colony algorithms for global numerical optimization. Expert Syst Appl. 2010;37:5682–7.CrossRef
12.
go back to reference Brajevic I, Tuba M, Subotic M. Improved artificial bee colony algorithm for constrained problems. In: Proceedings of the 11th WSEAS International conference on evolutionary computing, world scientific and engineering academy and society (WSEAS), Stevens Point, WI, USA, June 2010. p. 185–190. Brajevic I, Tuba M, Subotic M. Improved artificial bee colony algorithm for constrained problems. In: Proceedings of the 11th WSEAS International conference on evolutionary computing, world scientific and engineering academy and society (WSEAS), Stevens Point, WI, USA, June 2010. p. 185–190.
13.
go back to reference Brajevic I, Tuba M, Subotic M. Performance of the improved artificial bee colony algorithm on standard engineering constrained problems. Int J Math Comput Simul. 2011;5(2):135–43. Brajevic I, Tuba M, Subotic M. Performance of the improved artificial bee colony algorithm on standard engineering constrained problems. Int J Math Comput Simul. 2011;5(2):135–43.
14.
go back to reference Chang HS. Convergingmarriage in honey-bees optimization and application to stochastic dynamic programming. J Glob Optim. 2006;35(3):423–41.CrossRefMATH Chang HS. Convergingmarriage in honey-bees optimization and application to stochastic dynamic programming. J Glob Optim. 2006;35(3):423–41.CrossRefMATH
15.
go back to reference Chong CS, Low MYH, Sivakumar AI, Gay KL. A bee colony optimization algorithm to job shop scheduling. In: Proceedings of the winter simulation conference, Monterey, CA, USA, December 2006. p. 1954–1961. Chong CS, Low MYH, Sivakumar AI, Gay KL. A bee colony optimization algorithm to job shop scheduling. In: Proceedings of the winter simulation conference, Monterey, CA, USA, December 2006. p. 1954–1961.
16.
go back to reference Cicirello VA, Smith SF. Improved routing wasps for distributed factory control. In: Proceedings of IJCAI workshop on artificial intelligence and manufacturing, Seattle, WA, USA, August 2001. p. 26–32. Cicirello VA, Smith SF. Improved routing wasps for distributed factory control. In: Proceedings of IJCAI workshop on artificial intelligence and manufacturing, Seattle, WA, USA, August 2001. p. 26–32.
17.
go back to reference Cicirello VA, Smith SF. Wasp-like agents for distributed factory coordination. Auton Agents Multi-Agent Syst. 2004;8:237–66.CrossRef Cicirello VA, Smith SF. Wasp-like agents for distributed factory coordination. Auton Agents Multi-Agent Syst. 2004;8:237–66.CrossRef
18.
go back to reference Diwold K, Aderhold A, Scheidler A, Middendorf M. Performance evaluation of artificial bee colony optimization and new selection schemes. Memetic Comput. 2011;3:149–62.CrossRefMATH Diwold K, Aderhold A, Scheidler A, Middendorf M. Performance evaluation of artificial bee colony optimization and new selection schemes. Memetic Comput. 2011;3:149–62.CrossRefMATH
19.
go back to reference Drias H, Sadeg S, Yahi S. Cooperative bees swarm for solving the maximum weighted satisfiability problem. In: Computational intelligence and bioinspired systems, vol. 3512 of Lecture notes in computer science. Berlin: Springer; 2005. p. 318–325. Drias H, Sadeg S, Yahi S. Cooperative bees swarm for solving the maximum weighted satisfiability problem. In: Computational intelligence and bioinspired systems, vol. 3512 of Lecture notes in computer science. Berlin: Springer; 2005. p. 318–325.
20.
go back to reference Fister I, Fister Jr I, Zumer JB. Memetic artificial bee colony algorithm for large-scale global optimization. In: Proceedings of IEEE congress on evolutionary computation (CEC), Brisbane, Australia, June 2012. p. 1–8. Fister I, Fister Jr I, Zumer JB. Memetic artificial bee colony algorithm for large-scale global optimization. In: Proceedings of IEEE congress on evolutionary computation (CEC), Brisbane, Australia, June 2012. p. 1–8.
21.
22.
go back to reference Gao WF, Liu SY. A modified artificial bee colony algorithm. Comput Oper Res. 2012;39(3):687–97.CrossRefMATH Gao WF, Liu SY. A modified artificial bee colony algorithm. Comput Oper Res. 2012;39(3):687–97.CrossRefMATH
23.
go back to reference Haddad OB, Afshar A, Marino MA. Honey-bees mating optimization (HBMO) algorithm: a new heuristic approach for water resources optimization. Water Resour Manage. 2006;20(5):661–80.CrossRef Haddad OB, Afshar A, Marino MA. Honey-bees mating optimization (HBMO) algorithm: a new heuristic approach for water resources optimization. Water Resour Manage. 2006;20(5):661–80.CrossRef
24.
go back to reference Haijun D, Qingxian F. Artificial bee colony algorithm based on Boltzmann selection policy. Comput Eng Appl. 2009;45(31):53–5. Haijun D, Qingxian F. Artificial bee colony algorithm based on Boltzmann selection policy. Comput Eng Appl. 2009;45(31):53–5.
25.
go back to reference Kang F, Li J, Xu Q. Structural inverse analysis by hybrid simplex artificial bee colony algorithms. Comput Struct. 2009;87(13):861–70.CrossRef Kang F, Li J, Xu Q. Structural inverse analysis by hybrid simplex artificial bee colony algorithms. Comput Struct. 2009;87(13):861–70.CrossRef
26.
go back to reference Kang F, Li J, Ma Z. Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions. Inf Sci. 2011;181:3508–31.MathSciNetCrossRefMATH Kang F, Li J, Ma Z. Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions. Inf Sci. 2011;181:3508–31.MathSciNetCrossRefMATH
27.
go back to reference Karaboga D. An Idea based on honey bee swarm for numerical optimization. Technical Report, Erciyes University, Engineering Faculty Computer Engineering Department, Erciyes, Turkey, 2005. Karaboga D. An Idea based on honey bee swarm for numerical optimization. Technical Report, Erciyes University, Engineering Faculty Computer Engineering Department, Erciyes, Turkey, 2005.
28.
go back to reference Karaboga D, Akay B. A comparative study of artificial bee colony algorithm. Appl Math Comput. 2009;214:108–32.MathSciNetMATH Karaboga D, Akay B. A comparative study of artificial bee colony algorithm. Appl Math Comput. 2009;214:108–32.MathSciNetMATH
29.
go back to reference Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Glob Optim. 2007;39(3):459–71.MathSciNetCrossRefMATH Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Glob Optim. 2007;39(3):459–71.MathSciNetCrossRefMATH
30.
go back to reference Karaboga D, Basturk B. On the performance of artificial bee colony (ABC) algorithm. Appl Soft Comput. 2008;8(1):687–97.CrossRef Karaboga D, Basturk B. On the performance of artificial bee colony (ABC) algorithm. Appl Soft Comput. 2008;8(1):687–97.CrossRef
31.
go back to reference Karaboga D, Gorkemli B. A combinatorial artificial bee colony algorithm for traveling salesman problem. In: Proceedings of international symposium on innovations in intelligent systems and applications (INISTA), Istanbul, Turkey, June 2011. p. 50–53. Karaboga D, Gorkemli B. A combinatorial artificial bee colony algorithm for traveling salesman problem. In: Proceedings of international symposium on innovations in intelligent systems and applications (INISTA), Istanbul, Turkey, June 2011. p. 50–53.
32.
go back to reference Karaboga D, Gorkemli B. A quick artificial bee colony (qABC) algorithm and its performance on optimization problems. Appl Soft Comput. 2014;23:227–38.CrossRef Karaboga D, Gorkemli B. A quick artificial bee colony (qABC) algorithm and its performance on optimization problems. Appl Soft Comput. 2014;23:227–38.CrossRef
33.
go back to reference Karaboga D, Ozturk C, Karaboga N, Gorkemli B. Artificial bee colony programming for symbolic regression. Inf Sci. 2012;209:1–15.CrossRef Karaboga D, Ozturk C, Karaboga N, Gorkemli B. Artificial bee colony programming for symbolic regression. Inf Sci. 2012;209:1–15.CrossRef
34.
go back to reference Kashan MH, Nahavandi N, Kashan AH. DisABC: a new artificial bee colony algorithm for binary optimization. Appl Soft Comput. 2012;12:342–52.CrossRef Kashan MH, Nahavandi N, Kashan AH. DisABC: a new artificial bee colony algorithm for binary optimization. Appl Soft Comput. 2012;12:342–52.CrossRef
35.
go back to reference Kiran MS, Findik O. A directed artificial bee colony algorithm. Appl Soft Comput. 2015;26:454–62.CrossRef Kiran MS, Findik O. A directed artificial bee colony algorithm. Appl Soft Comput. 2015;26:454–62.CrossRef
36.
go back to reference Kiran MS. The continuous artificial bee colony algorithm for binary optimization. Appl Soft Comput. 2015;33:15–23.CrossRef Kiran MS. The continuous artificial bee colony algorithm for binary optimization. Appl Soft Comput. 2015;33:15–23.CrossRef
37.
go back to reference Li G, Niu P, Xiao X. Development and investigation of efficient artificial bee colony algorithm for numerical function optimization. Appl Soft Comput. 2012;12:320–32.CrossRef Li G, Niu P, Xiao X. Development and investigation of efficient artificial bee colony algorithm for numerical function optimization. Appl Soft Comput. 2012;12:320–32.CrossRef
38.
go back to reference Li X, Yang G. Artificial bee colony algorithm with memory. Appl Soft Comput. 2016;41:362–72.CrossRef Li X, Yang G. Artificial bee colony algorithm with memory. Appl Soft Comput. 2016;41:362–72.CrossRef
39.
go back to reference Liu Y, Passino KM. Biomimicry of social foraging bacteria for distributed optimization: models, principles, and emergent behaviors. J Optim Theor Appl. 2002;115(3):603–28.MathSciNetCrossRefMATH Liu Y, Passino KM. Biomimicry of social foraging bacteria for distributed optimization: models, principles, and emergent behaviors. J Optim Theor Appl. 2002;115(3):603–28.MathSciNetCrossRefMATH
40.
go back to reference Liu J, Zhu H, Ma Q, Zhang L, Xu H. An artificial bee colony algorithm with guide of global and local optima and asynchronous scaling factors for numerical optimization. Appl Soft Comput. 2015;37:608–18.CrossRef Liu J, Zhu H, Ma Q, Zhang L, Xu H. An artificial bee colony algorithm with guide of global and local optima and asynchronous scaling factors for numerical optimization. Appl Soft Comput. 2015;37:608–18.CrossRef
41.
go back to reference Lu X, Zhou Y. A novel global convergence algorithm: bee collecting pollen algorithm. In: Proceedings of the 4th international conference on intelligent computing, Shanghai, China, September 2008, vol. 5227 of Lecture notes in computer science. Berlin: Springer; 2008. p. 518–525. Lu X, Zhou Y. A novel global convergence algorithm: bee collecting pollen algorithm. In: Proceedings of the 4th international conference on intelligent computing, Shanghai, China, September 2008, vol. 5227 of Lecture notes in computer science. Berlin: Springer; 2008. p. 518–525.
42.
go back to reference Lucic P, Teodorovic D. Computing with bees: attacking complex transportation engineering problems. Int J Artif Intell Tools. 2003;12:375–94. Lucic P, Teodorovic D. Computing with bees: attacking complex transportation engineering problems. Int J Artif Intell Tools. 2003;12:375–94.
43.
go back to reference Mezura-Montes E, Velez-Koeppel RE. Elitist artificial bee colony for constrained real-parameter optimization. In: Proceedings of IEEE congress on evolutionary computation (CEC), Barcelona, Spain, July 2010. p. 1–8. Mezura-Montes E, Velez-Koeppel RE. Elitist artificial bee colony for constrained real-parameter optimization. In: Proceedings of IEEE congress on evolutionary computation (CEC), Barcelona, Spain, July 2010. p. 1–8.
44.
go back to reference Moayedikia A, Jensen R, Wiil UK, Forsati R. Weighted bee colony algorithm for discrete optimization problems with application to feature selection. Eng Appl Artif Intell. 2015;44:153–67.CrossRef Moayedikia A, Jensen R, Wiil UK, Forsati R. Weighted bee colony algorithm for discrete optimization problems with application to feature selection. Eng Appl Artif Intell. 2015;44:153–67.CrossRef
45.
go back to reference Moritz RFA, Southwick EE. Bees as super-organisms. Berlin, Germany: Springer; 1992.CrossRef Moritz RFA, Southwick EE. Bees as super-organisms. Berlin, Germany: Springer; 1992.CrossRef
46.
go back to reference Navrat P. Bee hive metaphor for web search. In: Proceedings of the international conference on computer systems and technologies (CompSysTech), Veliko Turnovo, Bulgaria, 2006. p. IIIA.12. Navrat P. Bee hive metaphor for web search. In: Proceedings of the international conference on computer systems and technologies (CompSysTech), Veliko Turnovo, Bulgaria, 2006. p. IIIA.12.
47.
go back to reference Ozturk C, Hancer E, Karaboga D. A novel binary artificial bee colony algorithm based on genetic operators. Inf Sci. 2015;297:154–70.MathSciNetCrossRef Ozturk C, Hancer E, Karaboga D. A novel binary artificial bee colony algorithm based on genetic operators. Inf Sci. 2015;297:154–70.MathSciNetCrossRef
48.
go back to reference Pham DT, Kog E, Ghanbarzadeh A, Otri S, Rahim S, Zaidi M. The bees algorithm—a novel tool for complex optimisation problems. In: Proceedings of the 2nd international virtual conference on intelligent production machines and systems (IPROMS), Cardiff, UK, July 2006. p. 454–459. Pham DT, Kog E, Ghanbarzadeh A, Otri S, Rahim S, Zaidi M. The bees algorithm—a novel tool for complex optimisation problems. In: Proceedings of the 2nd international virtual conference on intelligent production machines and systems (IPROMS), Cardiff, UK, July 2006. p. 454–459.
49.
go back to reference Quijano N, Passino KM. Honey bee social foraging algorithms for resource allocation, Part i: algorithm and theory; part ii: application. In: Proceedings of the American control conference, New York, NY, USA, July 2007. p. 3383–3388, 3389–3394. Quijano N, Passino KM. Honey bee social foraging algorithms for resource allocation, Part i: algorithm and theory; part ii: application. In: Proceedings of the American control conference, New York, NY, USA, July 2007. p. 3383–3388, 3389–3394.
50.
go back to reference Rajasekhar A, Abraham A, Pant M. Levy mutated artificial bee colony algorithm for global optimization. In: Proceedings of IEEE international conference on systems, man and cybernetics, Anchorage, AK, USA, October 2011. p. 665–662. Rajasekhar A, Abraham A, Pant M. Levy mutated artificial bee colony algorithm for global optimization. In: Proceedings of IEEE international conference on systems, man and cybernetics, Anchorage, AK, USA, October 2011. p. 665–662.
51.
go back to reference Seeley TD. The wisdom of the hive: the social physiology of honey bee colonies. Massachusetts: Harvard University Press; 1995. Seeley TD. The wisdom of the hive: the social physiology of honey bee colonies. Massachusetts: Harvard University Press; 1995.
52.
go back to reference Sharma H, Bansal JC, Arya KV. Opposition based Levy flight artificial bee colony. Memetic Comput. 2013;5:213–27.CrossRef Sharma H, Bansal JC, Arya KV. Opposition based Levy flight artificial bee colony. Memetic Comput. 2013;5:213–27.CrossRef
53.
go back to reference Sharma TK, Pant M. Enhancing the food locations in an artificial bee colony algorithm. Soft Comput. 2014;17:1939–65.CrossRef Sharma TK, Pant M. Enhancing the food locations in an artificial bee colony algorithm. Soft Comput. 2014;17:1939–65.CrossRef
54.
go back to reference Singh A. An artificial bee colony algorithm for the leaf-constrained minimum spanning tree problem. Applied Soft Comput. 2009;9(2):625–31.CrossRef Singh A. An artificial bee colony algorithm for the leaf-constrained minimum spanning tree problem. Applied Soft Comput. 2009;9(2):625–31.CrossRef
55.
go back to reference Stanarevic N, Tuba M, Bacanin N. Enhanced artificial bee colony algorithm performance. In: Proceedings of the 14th WSEAS international conference on computers, world scientific and engineering academy and society (WSEAS). Stevens Point, WI, USA, June 2010. p. 440–445. Stanarevic N, Tuba M, Bacanin N. Enhanced artificial bee colony algorithm performance. In: Proceedings of the 14th WSEAS international conference on computers, world scientific and engineering academy and society (WSEAS). Stevens Point, WI, USA, June 2010. p. 440–445.
56.
go back to reference Teo J, Abbass HA. A true annealing approach to the marriage in honey-bees optimization algorithm. Int J Comput Intell Appl. 2003;3:199–208.CrossRef Teo J, Abbass HA. A true annealing approach to the marriage in honey-bees optimization algorithm. Int J Comput Intell Appl. 2003;3:199–208.CrossRef
57.
go back to reference Teodorovic D, Dell’Orco M. Bee colony optimization—a cooperative learning approach to complex transportation problems. In: Proceedings of the 10th meeting of the EURO working group on transportation, Poznan, Poland, September 2005. p. 51–60. Teodorovic D, Dell’Orco M. Bee colony optimization—a cooperative learning approach to complex transportation problems. In: Proceedings of the 10th meeting of the EURO working group on transportation, Poznan, Poland, September 2005. p. 51–60.
58.
go back to reference Tsai P-W, Pan J-S, Liao B-Y, Chu S-C. Enhanced artificial bee colony optimization. Int J Innovative Comput Inf Control. 2009;5(12):5081–92. Tsai P-W, Pan J-S, Liao B-Y, Chu S-C. Enhanced artificial bee colony optimization. Int J Innovative Comput Inf Control. 2009;5(12):5081–92.
59.
go back to reference Wedde HF, Farooq M, Zhang Y. BeeHive: an efficient fault-tolerant routing algorithm inspired by honey bee behavior. In: Dorigo M, editors. Ant colony optimization and swarm intelligence, vol. 3172 of Lecture notes in computer science. Berlin: Springer; 2004. pp. 83–94. Wedde HF, Farooq M, Zhang Y. BeeHive: an efficient fault-tolerant routing algorithm inspired by honey bee behavior. In: Dorigo M, editors. Ant colony optimization and swarm intelligence, vol. 3172 of Lecture notes in computer science. Berlin: Springer; 2004. pp. 83–94.
60.
go back to reference Yang XS. Engineering optimizations via nature-inspired virtual bee algorithms. In: Mira J, lvarez JR, editors. Artificial intelligence and knowledge engineering applications: a bioinspired approach, vol. 3562 of Lecture notes in computer science. Berlin: Springer; 2005. pp. 317–323. Yang XS. Engineering optimizations via nature-inspired virtual bee algorithms. In: Mira J, lvarez JR, editors. Artificial intelligence and knowledge engineering applications: a bioinspired approach, vol. 3562 of Lecture notes in computer science. Berlin: Springer; 2005. pp. 317–323.
62.
go back to reference Zhu G, Kwong S. Gbest-guided artificial bee colony algorithm for numerical function optimization. Appl Math Comput. 2010;217:3166–73.MathSciNetMATH Zhu G, Kwong S. Gbest-guided artificial bee colony algorithm for numerical function optimization. Appl Math Comput. 2010;217:3166–73.MathSciNetMATH
Metadata
Title
Bee Metaheuristics
Authors
Ke-Lin Du
M. N. S. Swamy
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-41192-7_12

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