Large-scale global optimization via swarm intelligence

Book chapter

Cheng, S., Ting, T. and Yang, X. 2014. Large-scale global optimization via swarm intelligence. in: Solving Computationally Expensive Engineering Problems Springer.
Chapter titleLarge-scale global optimization via swarm intelligence
AuthorsCheng, S., Ting, T. and Yang, X.
LanguageEnglish
Book titleSolving Computationally Expensive Engineering Problems
PublisherSpringer
ISSN2194-1009
Publication dates
Print04 Sep 2014
Publication process dates
Deposited27 Apr 2016
Accepted19 Apr 2014
Output statusPublished
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-319-08985-0_10
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Chang, Y., Yi, J., Yan, W., Yang, X., Zhang, S., Gao, Y. and Wang, X. 2014. Oil supply between OPEC and non-OPEC based on game theory. International Journal of Systems Science. 45 (10), pp. 2127-2132. https://doi.org/10.1080/00207721.2012.762562
Bat algorithm is better than intermittent search strategy
Yang, X., Deb, S. and Fong, S. 2014. Bat algorithm is better than intermittent search strategy. Journal of Multiple-Valued Logic and Soft Computing. 22 (3), pp. 223-237.
Nature-inspired framework for hyperspectral band selection
Nakamura, R., Garcia Fonseca, L., Dos Santos, J., Da S. Torres, R., Yang, X. and Papa, J. 2014. Nature-inspired framework for hyperspectral band selection. IEEE Transactions on Geoscience and Remote Sensing. 52 (4), pp. 2126-2137. https://doi.org/10.1109/TGRS.2013.2258351
A discrete firefly algorithm for the multi-objective hybrid flowshop scheduling problems
Marichelvam, M., Prabaharan, T. and Yang, X. 2014. A discrete firefly algorithm for the multi-objective hybrid flowshop scheduling problems. IEEE Transactions on Evolutionary Computation. 18 (2), pp. 301-305. https://doi.org/10.1109/TEVC.2013.2240304
Binary bat algorithm
Mirjalili, S., Mirjalili, S. and Yang, X. 2014. Binary bat algorithm. Neural Computing and Applications. 25 (3-4), pp. 663-681. https://doi.org/10.1007/s00521-013-1525-5
Bat algorithm based on simulated annealing and Gaussian perturbations
He, X., Ding, W. and Yang, X. 2014. Bat algorithm based on simulated annealing and Gaussian perturbations. Neural Computing and Applications. 25 (2), pp. 459-468. https://doi.org/10.1007/s00521-013-1518-4
Discrete cuckoo search algorithm for the travelling salesman problem
Ouaarab, A., Ahiod, B. and Yang, X. 2014. Discrete cuckoo search algorithm for the travelling salesman problem. Neural Computing and Applications. 24 (7-8), pp. 1659-1669. https://doi.org/10.1007/s00521-013-1402-2
Cuckoo search: recent advances and applications
Yang, X. and Deb, S. 2014. Cuckoo search: recent advances and applications. Neural Computing and Applications. 24 (1), pp. 169-174. https://doi.org/10.1007/s00521-013-1367-1
Chaotic bat algorithm
Gandomi, A. and Yang, X. 2014. Chaotic bat algorithm. Journal of Computational Science. 5 (2), pp. 224-232. https://doi.org/10.1016/j.jocs.2013.10.002
An empirical study of test effort estimation based on bat algorithm
Srivastava, P., Bidwai, A., Khan, A., Rathore, K., Sharma, R. and Yang, X. 2014. An empirical study of test effort estimation based on bat algorithm. International Journal of Bio-Inspired Computation. 6 (1), pp. 57-70. https://doi.org/10.1504/IJBIC.2014.059966
Bio-inspired computation: success and challenges of IJBIC
Yang, X. and Cui, Z. 2014. Bio-inspired computation: success and challenges of IJBIC. International Journal of Bio-Inspired Computation. 6 (1), pp. 1-6. https://doi.org/10.1504/IJBIC.2014.059969
A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest
Rodrigues, D., Pereira, L., Nakamura, R., Costa, K., Yang, X., Souza, A. and Papa, J. 2014. A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest. Expert Systems with Applications. 41 (5), pp. 2250-2258. https://doi.org/10.1016/j.eswa.2013.09.023
A bio-inspired algorithm for identification of critical components in the transportation networks
Zhang, X., Adamatzky, A., Yang, H., Mahadaven, S., Yang, X., Wang, Q. and Deng, Y. 2014. A bio-inspired algorithm for identification of critical components in the transportation networks. Applied Mathematics and Computation. 248, pp. 18-27. https://doi.org/10.1016/j.amc.2014.09.055
A firefly-inspired method for protein structure prediction in lattice models
Maher, B., Albrecht, A., Loomes, M., Yang, X. and Steinhofel, K. 2014. A firefly-inspired method for protein structure prediction in lattice models. Biomolecules. 4 (1), pp. 56-75. https://doi.org/10.3390/biom4010056
True global optimality of the pressure vessel design problem: a benchmark for bio-inspired optimisation algorithms
Yang, X., Huyck, C., Karamanoglu, M. and Khan, N. 2013. True global optimality of the pressure vessel design problem: a benchmark for bio-inspired optimisation algorithms. International Journal of Bio-Inspired Computation. 5 (6), pp. 329-335. https://doi.org/10.1504/IJBIC.2013.058910
Applications and analysis of bio-inspired eagle strategy for engineering optimization
Yang, X., Karamanoglu, M., Ting, T. and Zhao, Y. 2014. Applications and analysis of bio-inspired eagle strategy for engineering optimization. Neural Computing and Applications. 25 (2), pp. 411-420. https://doi.org/10.1007/s00521-013-1508-6
Flower pollination algorithm: a novel approach for multiobjective optimization
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Random walks, Lévy flights, Markov chains and metaheuristic optimization
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Are motorways rational from slime mould's point of view?
Adamatzky, A., Akl, S., Alonso-Sanz, R., Van Dessel, W., Ibrahim, Z., Ilachinski, A., Jones, J., Kayem, A., Martínez, G., De Oliveira, P., Prokopenko, M., Schubert, T., Sloot, P., Strano, E. and Yang, X. 2013. Are motorways rational from slime mould's point of view? International Journal of Parallel, Emergent and Distributed Systems. 28 (3), pp. 230-248. https://doi.org/10.1080/17445760.2012.685884
Advances in simulation-driven optimization and modelling
Koziel, S., Leifsson, L. and Yang, X. 2012. Advances in simulation-driven optimization and modelling. Journal of Computational Methods in Science and Engineering. 12 (1-2), pp. 1-4. https://doi.org/10.3233/JCM-2012-0400
Metaheuristic algorithms for self-organizing systems: a tutorial
Yang, X. 2012. Metaheuristic algorithms for self-organizing systems: a tutorial. in: Self-Adaptive and Self-Organizing Systems (SASO), 2012 IEEE Sixth International Conference on IEEE Conference Publications. pp. 249 -250
Rare events forecasting using a residual-feedback GMDH neural network
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Integrating nature-inspired optimization algorithms to K-means clustering
Tang, R., Fong, S., Yang, X. and Deb, S. 2012. Integrating nature-inspired optimization algorithms to K-means clustering. in: Seventh International Conference on Digital Information Management (ICDIM), IEEE Conference Publications. pp. 116-123
Wolf search algorithm with ephemeral memory
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Metaheuristic applications in structures and infrastructures
Gandom, A., Yang, X., Talatahari, S. and Alavi, A. 2013. Metaheuristic applications in structures and infrastructures. Elsevier.
Multi-objective flower algorithm for optimization
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Optimal test sequence generation using firefly algorithm
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Multiobjective firefly algorithm for continuous optimization
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Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems
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Multiobjective cuckoo search for design optimization
Yang, X. and Deb, S. 2013. Multiobjective cuckoo search for design optimization. Computers and Operations Research. 40 (6), pp. 1616-1624. https://doi.org/10.1016/j.cor.2011.09.026
Firefly algorithms for multimodal optimization
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Cuckoo search via Lévy flights
Yang, X. and Deb, S. 2009. Cuckoo search via Lévy flights. in: World Congress on Nature & Biologically Inspired Computing (NaBIC 2009) IEEE Publications. pp. 210-214
Flower pollination algorithm for global optimization
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Parameter estimation from laser flash experiment data
Wright, L., Yang, X., Matthews, C., Chapman, L. and Roberts, S. 2011. Parameter estimation from laser flash experiment data. in: Computational optimization and applications in engineering and industry studies in computational intelligence Berlin Springer.
Benchmark problems in structural optimization
Gandomi, A. and Yang, X. 2011. Benchmark problems in structural optimization. in: Koziel, S. and Yang, X. (ed.) Computational optimization, methods and algorithms Springer.
Computational optimization: an overview
Yang, X. and Koziel, S. 2011. Computational optimization: an overview. in: Computational Optimization, Methods and Algorithms Springer.
Engineering optimisation by cuckoo search
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Engineering optimization: an introduction with metaheuristic applications
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Metaheuristics in water, geotechnical and transport engineering
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Bat algorithm for topology optimization in microelectronic applications
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Cuckoo search for business optimization applications
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Bat algorithm for constrained optimization tasks
Gandomi, A., Yang, X., Alavi, A. and Talatahari, S. 2012. Bat algorithm for constrained optimization tasks. Neural Computing and Applications. 22 (6), pp. 1239-1255. https://doi.org/10.1007/s00521-012-1028-9
Efficiency analysis of swarm intelligence and randomization techniques
Yang, X. 2012. Efficiency analysis of swarm intelligence and randomization techniques. Journal of Computational and Theoretical Nanoscience. 9 (2), pp. 189-198. https://doi.org/10.1166/jctn.2012.2012
Modelling of a pulsating heat pipe and start up asymptotics
Yang, X. and Luan, T. 2012. Modelling of a pulsating heat pipe and start up asymptotics. Procedia Computer Science. 9, pp. 784-791. https://doi.org/10.1016/j.procs.2012.04.084
Computational optimization, modelling and simulation: smart algorithms and better models
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Free lunch or no free lunch: that is not just a question?
Yang, X. 2012. Free lunch or no free lunch: that is not just a question? International Journal on Artificial Intelligence Tools. 21 (3). https://doi.org/10.1142/S0218213012400106
Coupled eagle strategy and differential evolution for unconstrained and constrained global optimization
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Bat algorithm: a novel approach for global engineering optimization
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Evolutionary boundary constraint handling scheme
Gandomi, A. and Yang, X. 2012. Evolutionary boundary constraint handling scheme. Neural Computing and Applications. 21 (6), pp. 1449-1462. https://doi.org/10.1007/s00521-012-1069-0
Two-stage eagle strategy with differential evolution
Yang, X. and Deb, S. 2012. Two-stage eagle strategy with differential evolution. International Journal of Bio-Inspired Computation. 4 (1), pp. 1-5. https://doi.org/10.1504/IJBIC.2012.044932
Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect
Yang, X., Hosseini, S. and Gandomi, A. 2012. Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect. Applied Soft Computing. 12 (3), pp. 1180-1186. https://doi.org/10.1016/j.asoc.2011.09.017
Accelerated particle swarm optimization and support vector machine for business optimization and applications
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Bat algorithm for multi-objective optimisation
Yang, X. 2011. Bat algorithm for multi-objective optimisation. International Journal of Bio-Inspired Computation. 3 (5), pp. 267-274. https://doi.org/10.1504/IJBIC.2011.042259
Mixed variable structural optimization using Firefly Algorithm
Gandomi, A., Yang, X. and Alavi, A. 2011. Mixed variable structural optimization using Firefly Algorithm. Computers and Structures. 89 (23-24), pp. 2325-2336. https://doi.org/10.1016/j.compstruc.2011.08.002
A new metaheuristic bat-inspired algorithm
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Eagle strategy using Lévy walk and firefly algorithm for stochastic optimization
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Optimization and data mining for fracture prediction in geosciences
Shi, G. and Yang, X. 2010. Optimization and data mining for fracture prediction in geosciences. Procedia Computer Science. 1 (1), pp. 1359-1366. https://doi.org/10.1016/j.procs.2010.04.151
Firefly algorithm, stochastic test functions and design optimisation
Yang, X. 2010. Firefly algorithm, stochastic test functions and design optimisation. International Journal of Bio-Inspired Computation. 2 (2), pp. 78-84. https://doi.org/10.1504/IJBIC.2010.032124
Oil and gas assessment of the Kuqa depression of Tarim Basin in western China by simple fluid flow models of primary and secondary migrations of hydrocarbons
Shi, G., Zhang, Q., Yang, X. and Mi, S. 2010. Oil and gas assessment of the Kuqa depression of Tarim Basin in western China by simple fluid flow models of primary and secondary migrations of hydrocarbons. Journal of Petroleum Science and Engineering. 75 (1-2), pp. 77-90. https://doi.org/10.1016/j.petrol.2010.10.009