Abstract
In this paper, an adaptive hybrid genetic algorithm with modified cuckoo search (MCS-AHGA) is proposed for effectively solving reliability optimization problems. For the proposed MCS-AHGA, a modified cuckoo search (MCS) which improves a weakness of conventional cuckoo search (CS) is adapted, and the genetic algorithm with an adaptive search scheme (AGA) is used. Hybridizing the MCS and the AGA can reinforce search quality and speed toward global optimal solution rather than hybridizing conventional CS and GA does. In numerical experiment, three types of reliability optimization problems are used for comparing the performance of the proposed MCS-AHGA with those of various conventional competing approaches including CS and GA. The experimental result proves that the proposed MCS-AHGA outperforms the competing conventional algorithms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gen M, Yun Y (2006) Soft computing approach for reliability optimization: state-of-the-art survey. Reliab Eng Syst Saf 91(9):1008–1026
Kuo W, Wan R (2007) Recent advances in optimal reliability allocation. In: Computational intelligence in reliability engineering. Springer, pp 1–36
Kanagaraj G, Ponnambalam S, Jawahar N (2013) A hybrid cuckoo search and genetic algorithm for reliability-redundancy allocation problems. Comput Ind Eng 66(4):1115–1124
Valian E (2014) Solving reliability optimization problems by cuckoo search. In: Cuckoo search and firefly algorithm. Springer, pp 195–215
Valian E, Tavakoli S, Mohanna S, Haghi A (2013) Improved cuckoo search for reliability optimization problems. Comput Ind Eng 64(1):459–468
Prasad V, Kuo W (2000) Reliability optimization of coherent systems. IEEE Trans Reliab 49(3):323–330
Geoffrion AM (1969) An improved implicit enumeration approach for integer programming. Oper Res 17(3):437–454
Kuo W (2001) Optimal reliability design: fundamentals and applications. Cambridge University Press, Cambridge
Ha C, Kuo W (2005) Multi-path approach for reliability-redundancy allocation using a scaling method. J Heuristics 11(3):201–217
Agarwal M, Sharma VK (2010) Ant colony approach to constrained redundancy optimization in binary systems. Appl Math Model 34(4):992–1003
ChangYoon L, YoungSu Y (2002) Reliability optimization design for complex systems by hybrid ga with fuzzy logic control and local search. IEICE Trans Fundam Electron Commun Comput Sci 85(4):880–891
Kulturel-Konak S, Smith AE, Coit DW (2003) Efficiently solving the redundancy allocation problem using tabu search. IIE Trans 35(6):515–526
Vo Bay, Hong TP, Le B (2009) An efficient particle swarm approach for mixed-integer programming in reliability-redundancy optimization applications. Reliab Eng Syst Saf 94(4):830–837
Tavakkoli-Moghaddam R, Safari J, Sassani F (2008) Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm. Reliab Eng Syst Saf 93(4):550–556
Wu P, Gao L et al (2011) An improved particle swarm optimization algorithm for reliability problems. ISA Trans 50(1):71–81
Zou D, Gao L et al (2011) An effective global harmony search algorithm for reliability problems. Expert Syst Appl 38(4):4642–4648
Gen M, Cheng R (2000) Genetic algorithms and engineering optimization, vol 7. Wiley, New York
Gen M, Kim JR (1999) GA-based reliability design: state-of-the-art survey. Comput Ind Eng 37(1):151–155
ChangYoon L, Way K (2001) Reliability optimization design using a hybridized genetic algorithm with a neural-network technique. IEICE Trans Fundam Electron Commun Comput Sci 84(2):627–637
Mukuda M, Yun Y, Gen M (2004) Adaptive genetic local search algorithms for solving reliability optimization problems. IEEJ Trans Electron Inf Syst 124(10):1986–1990
Mak K, Wong Y, Wang X (2000) An adaptive genetic algorithm for manufacturing cell formation. Int J Adv Manuf Technol 16(7):491–497
Song Y, Wang G, Wang P, Johns A (1997) Environmental/economic dispatch using fuzzy logic controlled genetic algorithms. In: Generation, transmission and distribution, IEE proceedings, IET, vol 144, pp 377–382
Srinivas M, Patnaik LM (1994) Adaptive probabilities of crossover and mutation in genetic algorithms. IEEE Trans Syst Man Cybern 24(4):656–667
Yun Y, Gen M (2003) Performance analysis of adaptive genetic algorithms with fuzzy logic and heuristics. Fuzzy Optim Decis Mak 2(2):161–175
Li B, Jiang W (2000) A novel stochastic optimization algorithm. IEEE Trans Syst Man Cybern Part B Cybern 30(1):193–198
Yang XS, Deb S, (2009) Cuckoo search via lévy flights. In: World congress on nature & biologically inspired computing, (2009) NaBIC 2009. IEEE, pp 210–214
Yun YS (2005) Study on adaptive hybrid genetic algorithm and its applications to engineering design problems
Yun Y, Gen M, Seo S (2003) Various hybrid methods based on genetic algorithm with fuzzy logic controller. J Intell Manuf 14(3–4):401–419
Yang XS (2013) Cuckoo search and firefly algorithm: theory and applications, vol 516. Springer, Switzerland
Ravi V, Murty B, Reddy P (1997) Nonequilibrium simulated-annealing algorithm applied to reliability optimization of complex systems. IEEE Trans Reliab 46(2):233–239
Yun YS, Jo JB, Gen M (2015) Hybridization of modified cuckoo search and genetic algorithm for reliability optimization problems. In: 45th international conference on computers and industrial engineering, (CIE45), pp 1–13
Acknowledgments
This work is partly supported by JSPS: Grant-in-Aid for Scientific Research (C; No. 15K00357) and by the National Research Foundation of Korea Grant funded by the Korean Government (NRF- 2014S1A5A2A01010951). This paper is a revised and extended version of the paper which was presented in 45th International Conference on Computers and Industrial Engineering, Metz, France, 2015.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media Singapore
About this paper
Cite this paper
Yun, Y., Jo, J., Gen, M. (2017). Adaptive Hybrid Genetic Algorithm with Modified Cuckoo Search for Reliability Optimization Problem. In: Xu, J., Hajiyev, A., Nickel, S., Gen, M. (eds) Proceedings of the Tenth International Conference on Management Science and Engineering Management. Advances in Intelligent Systems and Computing, vol 502. Springer, Singapore. https://doi.org/10.1007/978-981-10-1837-4_31
Download citation
DOI: https://doi.org/10.1007/978-981-10-1837-4_31
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-1836-7
Online ISBN: 978-981-10-1837-4
eBook Packages: EngineeringEngineering (R0)