Dr Xin-She Yang


Dr Xin-She Yang
NameDr Xin-She Yang
Contact categoryResearcher
Job titleAssociate Professor in Simulation & Modelling
Research institute
Primary appointmentDesign Engineering & Mathematics
Email addressx.yang@mdx.ac.uk
ORCIDhttps://orcid.org/0000-0001-8231-5556 (unauthenticated)

Biography

Biography

Reader in Modelling and Simulation. 

Fellow of the Institute of Mathematics and its Applications (FIMA).

Teaching

PDE4905 Engineering Simulation (Master Level)

PDE1803 Engineering Mathematics and its Applications

PDE1140 Practical Applications of Mathematics for Engineers

MSO3550 Mathematical Techniques for Optimization 

MSO3200 Partial Differential Equations

MSO1155 Mathematical Models 

Research projects for PhD students (Parameter tuning, nature-inspired computing, artificial intelligence and machine learning algorithms, optimization, and engineering simulation, mathematical modelling, etc.)

Education and qualifications

DPhil in Applied Mathematics
University of Oxford

Grants

Multiple Research Grants Supported by National Measurement Office (NMO), EuroMet, NPL, Southwest Development Agency (UK) and industrial partners

Prizes and Awards

Highly cited researcher

Web of Science

UK Leader Award in Computer Science

Research.com

External activities

Panel Member for UKRI Doctoral Training Centres for AI Research
Reviewer for funding applications

External Reviewer for Research Councils in Iceland, Ireland, Austria, Brazil, Czech, European Science Foundation, and Switzerland
Reviewer for funding applications
Multiple National Research Councils

Book Series Editor for Springer Tracts on Nature-Inspired Computing
External committee
https://www.springer.com/series/16134

Research outputs

Cognitive beamforming design for dual-function radar-communications

Le, T., Ku, I., Yang, X., Masouros, C. and Le-Ngoc, T. 2024. Cognitive beamforming design for dual-function radar-communications. 2024 IEEE 99th Vehicular Technology Conference. Singapore 24 - 27 Jun 2024 IEEE.

Generalized Firefly Algorithm for optimal transmit beamforming

Le, T. and Yang, X. 2023. Generalized Firefly Algorithm for optimal transmit beamforming. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/TWC.2023.3328713

Review of parameter tuning methods for nature-inspired algorithms

Joy, G., Huyck, C. and Yang, X. 2023. Review of parameter tuning methods for nature-inspired algorithms. in: Yang, X. (ed.) Benchmarks and Hybrid Algorithms in Optimization and Applications Singapore Springer. pp. 33-47

A rank-one optimization framework and its applications to transmit beamforming

Le, T., Ng, D. and Yang, X. 2024. A rank-one optimization framework and its applications to transmit beamforming. IEEE Transactions on Vehicular Technology. 73 (1), pp. 620-636. https://doi.org/10.1109/TVT.2023.3303623

Firefly algorithm for beamforming design in RIS-aided communication systems

Le, T. and Yang, X. 2023. Firefly algorithm for beamforming design in RIS-aided communication systems. The 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring). Florence, Italy 20 - 23 Jun 2023 IEEE. https://doi.org/10.1109/VTC2023-Spring57618.2023.10201127

Flower pollination algorithm with pollinator attraction

Mergos, P. and Yang, X. 2022. Flower pollination algorithm with pollinator attraction. Evolutionary Intelligence. https://doi.org/10.1007/s12065-022-00700-7

An elitism-based multi-objective evolutionary algorithm for min-cost network disintegration

Li, Q., Liu, S., Bai, Y., He, X. and Yang, X. 2022. An elitism-based multi-objective evolutionary algorithm for min-cost network disintegration. Knowledge-Based Systems. 239, pp. 1-19. https://doi.org/10.1016/j.knosys.2021.107944

MO-MFCGA: Multiobjective multifactorial cellular genetic algorithm for evolutionary multitasking

Osaba, E., Del Ser, J., Martinez, A., Lobo, J., Nebro, A. and Yang, X. 2021. MO-MFCGA: Multiobjective multifactorial cellular genetic algorithm for evolutionary multitasking. 2021 IEEE Symposium Series on Computational Intelligence (SSCI). Orlando, FL, USA 05 - 07 Dec 2021 IEEE. pp. 1-8 https://doi.org/10.1109/ssci50451.2021.9660024

Flower pollination algorithm parameters tuning

Mergos, P. and Yang, X. 2021. Flower pollination algorithm parameters tuning. Soft Computing. 25 (22), pp. 14429-14447. https://doi.org/10.1007/s00500-021-06230-1

Swarm and stochastic computing for global optimization

Yang, X. 2021. Swarm and stochastic computing for global optimization. in: Adamatzky, A. (ed.) Handbook of Unconventional Computing - Volume 1: Theory World Scientific. pp. 469-487

White learning methodology: a case study of cancer-related disease factors analysis in real-time PACS environment

Li, T., Fong, S., Siu, S., Yang, X., Liu, L. and Mohammed, S. 2020. White learning methodology: a case study of cancer-related disease factors analysis in real-time PACS environment. Computer Methods and Programs in Biomedicine. 197, pp. 1-18. https://doi.org/10.1016/j.cmpb.2020.105724

A nature-inspired feature selection approach based on hypercomplex information

de Rosa, G., Papa, J. and Yang, X. 2020. A nature-inspired feature selection approach based on hypercomplex information. Applied Soft Computing. 94. https://doi.org/10.1016/j.asoc.2020.106453

Nature-inspired optimization algorithms: challenges and open problems

Yang, X. 2020. Nature-inspired optimization algorithms: challenges and open problems. Journal of Computational Science. 46. https://doi.org/10.1016/j.jocs.2020.101104

Influence of initialization on the performance of metaheuristic optimizers

Li, Q., Liu, S. and Yang, X. 2020. Influence of initialization on the performance of metaheuristic optimizers. Applied Soft Computing. 91. https://doi.org/10.1016/j.asoc.2020.106193

Atomic scheduling of appliance energy consumption in residential smart grids

Kim, K., Lee, S., Ting, T. and Yang, X. 2019. Atomic scheduling of appliance energy consumption in residential smart grids. Energies. 12 (19). https://doi.org/10.3390/en12193666

Improved tabu search and simulated annealing methods for nonlinear data assimilation

Nino-Ruiz, E. and Yang, X. 2019. Improved tabu search and simulated annealing methods for nonlinear data assimilation. Applied Soft Computing. 83, p. 105624. https://doi.org/10.1016/j.asoc.2019.105624

Comparison of constraint-handling techniques for metaheuristic optimization

He, X.-S., Fan, Q.-W., Karamanoglu, M. and Yang, X. 2019. Comparison of constraint-handling techniques for metaheuristic optimization. 19th International Conference on Computational Science - ICCS 2019. Faro, Portugal 12 - 14 Jun 2019 Switzerland Springer. pp. 357-366 https://doi.org/10.1007/978-3-030-22744-9_28

Enhancing security of MME handover via fractional programming and Firefly algorithm

Vien, Q., Le, T., Yang, X. and Duong, T. 2019. Enhancing security of MME handover via fractional programming and Firefly algorithm. IEEE Transactions on Communications. 67 (9), pp. 6206-6220. https://doi.org/10.1109/TCOMM.2019.2920353

Bio-inspired computation: where we stand and what's next

Del Ser, J., Osaba, E., Molina, D., Yang, X., Salcedo-Sanz, S., Camacho, D., Das, S., Suganthan, P., Coello Coello, C. and Herrera, F. 2019. Bio-inspired computation: where we stand and what's next. Swarm and Evolutionary Computation. 48, pp. 220-250. https://doi.org/10.1016/j.swevo.2019.04.008

Optimization Techniques and Applications with Examples

Yang, X. 2018. Optimization Techniques and Applications with Examples. Hoboken, New Jersey John Wiley & Sons, Inc..

Global convergence analysis of the bat algorithm using a markovian framework and dynamical system theory

Chen, S., Peng, G., He, X. and Yang, X. 2018. Global convergence analysis of the bat algorithm using a markovian framework and dynamical system theory. Expert Systems with Applications. 114, pp. 173-182. https://doi.org/10.1016/j.eswa.2018.07.036

Metaheuristic optimization of reinforced concrete footings

Nigdeli, S., Bekdaş, G. and Yang, X. 2018. Metaheuristic optimization of reinforced concrete footings. KSCE Journal of Civil Engineering. 22 (11), pp. 4555-4563. https://doi.org/10.1007/s12205-018-2010-6

Self-adaptive decision-making mechanisms to balance the execution of multiple tasks for a multi-robots team

Palmieri, N., Yang, X., Rango, F. and Santamaria, A. 2018. Self-adaptive decision-making mechanisms to balance the execution of multiple tasks for a multi-robots team. Neurocomputing. https://doi.org/10.1016/j.neucom.2018.03.038

Discussion of “Estimation of Reference Evapotranspiration Using Neural Networks and Cuckoo Search Algorithm” by Shahaboddin Shamshirband, Mohsen Amirmojahedi, Milan Gocić, Shatirah Akib, Dalibor Petković, Jamshid Piri, and Slavisa Trajkovic

Fister, I., Fister, I. and Yang, X. 2018. Discussion of “Estimation of Reference Evapotranspiration Using Neural Networks and Cuckoo Search Algorithm” by Shahaboddin Shamshirband, Mohsen Amirmojahedi, Milan Gocić, Shatirah Akib, Dalibor Petković, Jamshid Piri, and Slavisa Trajkovic. Journal of Irrigation and Drainage Engineering. 144 (2), p. 07017023. https://doi.org/10.1061/(asce)ir.1943-4774.0001270

Mathematics for civil engineers: an introduction

Yang, X. 2017. Mathematics for civil engineers: an introduction. Edinburgh Dunedin Academic Press.

Optimisation of relay placement in wireless butterfly networks

Vien, Q. 2017. Optimisation of relay placement in wireless butterfly networks. in: Yang, X. (ed.) Nature-Inspired Algorithms and Applied Optimization Springer International Publishing.

Swarm robotics in wireless distributed protocol design for coordinating robots involved in cooperative tasks

De Rango, F., Palmieri, N., Yang, X. and Marano, S. 2018. Swarm robotics in wireless distributed protocol design for coordinating robots involved in cooperative tasks. Soft Computing. 22 (13), pp. 4251-4266. https://doi.org/10.1007/s00500-017-2819-9

How meta-heuristic algorithms contribute to deep learning in the hype of big data analytics

Fong, S., Deb, S. and Yang, X. 2018. How meta-heuristic algorithms contribute to deep learning in the hype of big data analytics. ICACNI 2016: 4th International Conference on Advanced Computing, Networking and Informatics. Odisha , India 22 - 24 Sep 2016 Springer. https://doi.org/10.1007/978-981-10-3373-5_1

Quaternion-based deep belief networks fine-tuning

Papa, J., Rosa, G., Pereira, D. and Yang, X. 2017. Quaternion-based deep belief networks fine-tuning. Applied Soft Computing. 60, pp. 328-335. https://doi.org/10.1016/j.asoc.2017.06.046

Handling dropout probability estimation in convolution neural networks using meta-heuristics

De Rosa, G., Papa, J. and Yang, X. 2018. Handling dropout probability estimation in convolution neural networks using meta-heuristics. Soft Computing. 22 (18), pp. 6147-6156. https://doi.org/10.1007/s00500-017-2678-4

On the handover security key update and residence management in LTE networks

Vien, Q., Le, T., Yang, X. and Duong, T. 2017. On the handover security key update and residence management in LTE networks. IEEE Wireless Communications and Networking Conference (WCNC 2017). San Francisco, CA, USA 19 - 22 Mar 2017 IEEE. pp. 1-6 https://doi.org/10.1109/WCNC.2017.7925678

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Palmieri, N., Yang, X., De Rango, F. and Marano, S. 2019. Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption. Neural Computing and Applications. 31 (1), pp. 263-286. https://doi.org/10.1007/s00521-017-2998-4

Nature-inspired computing and optimization: theory and applications

Patnaik, S., Yang, X. and Nakamatsu, K. (ed.) 2017. Nature-inspired computing and optimization: theory and applications. Springer.

Global convergence analysis of the flower pollination algorithm: a Discrete-Time Markov Chain Approach

He, X., Yang, X., Karamanoglu, M. and Zhao, Y. 2017. Global convergence analysis of the flower pollination algorithm: a Discrete-Time Markov Chain Approach. International Conference on Computational Science, ICCS 2017. Zurich, Switzerland 12 - 14 Jun 2017 Elsevier. https://doi.org/10.1016/j.procs.2017.05.020

New directional bat algorithm for continuous optimization problems

Chakri, A., Khelif, R., Benouaret, M. and Yang, X. 2017. New directional bat algorithm for continuous optimization problems. Expert Systems with Applications. 69, pp. 159-175. https://doi.org/10.1016/j.eswa.2016.10.050

A novel hybrid firefly algorithm for global optimization

Zhang, L., Liu, L., Yang, X. and Dai, Y. 2016. A novel hybrid firefly algorithm for global optimization. PLoS ONE. 11 (9), pp. 1-17. https://doi.org/10.1371/journal.pone.0163230

From swarm intelligence to metaheuristics: nature-inspired optimization algorithms

Yang, X., Deb, S., Fong, S., He, X. and Zhao, Y. 2016. From swarm intelligence to metaheuristics: nature-inspired optimization algorithms. Computer. 49 (9), pp. 52-59. https://doi.org/10.1109/MC.2016.292

Bio-inspired computation and applications in image processing

Yang, X. and Papa, J. 2016. Bio-inspired computation and applications in image processing. Academic Press.

Nature-inspired computation: an unconventional approach to optimization

Yang, X. 2016. Nature-inspired computation: an unconventional approach to optimization. in: Adamatzky, A. (ed.) Advances in Unconventional Computing - Volume 2: Prototypes, Models and Algorithms Cham Springer.

EEG-based person identification through binary flower pollination algorithm

Rodrigues, D., Silva, G., Papa, J., Marana, A. and Yang, X. 2016. EEG-based person identification through binary flower pollination algorithm. Expert Systems with Applications. 62, pp. 81-90. https://doi.org/10.1016/j.eswa.2016.06.006

Hybrid local diffusion maps and improved cuckoo search algorithm for multiclass dataset analysis

Jia, B., Yu, B., Wu, Q., Yang, X., Wei, C., Law, R. and Fu, S. 2016. Hybrid local diffusion maps and improved cuckoo search algorithm for multiclass dataset analysis. Neurocomputing. 189, pp. 106-116. https://doi.org/10.1016/j.neucom.2015.12.066

A physarum-inspired approach to supply chain network design

Zhang, X., Adamatzky, A., Yang, X., Yang, H., Mahadevan, S. and Deng, Y. 2016. A physarum-inspired approach to supply chain network design. Science China Information Sciences. 59. https://doi.org/10.1007/s11432-015-5417-4

Nature-inspired computation in engineering

Yang, X. (ed.) 2016. Nature-inspired computation in engineering. Springer.

Nature-inspired optimization algorithms in engineering: overview and applications

Yang, X. and He, X. 2016. Nature-inspired optimization algorithms in engineering: overview and applications. in: Yang, X. (ed.) Nature-Inspired Computation in Engineering Springer.

Parameterless bat algorithm and its performance study

Fister, I., Mlakar, U., Yang, X. and Fister, I. 2016. Parameterless bat algorithm and its performance study. in: Nature-Inspired Computation in Engineering Springer.

Cuckoo search: from Cuckoo reproduction strategy to combinatorial optimization

Ouaarab, A. and Yang, X. 2016. Cuckoo search: from Cuckoo reproduction strategy to combinatorial optimization. in: Nature-Inspired Computation in Engineering Springer.

Randomly attracted firefly algorithm with neighborhood search and dynamic parameter adjustment mechanism

Wang, H., Cui, Z., Sun, H., Rahnamayan, S. and Yang, X. 2017. Randomly attracted firefly algorithm with neighborhood search and dynamic parameter adjustment mechanism. Soft Computing. 21 (18), pp. 5325-5339. https://doi.org/10.1007/s00500-016-2116-z

A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy

Osaba, E., Yang, X., Diaz, F., Onieva, E., Masegosa, A. and Perallos, A. 2017. A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy. Soft Computing. 21 (18), pp. 5295-5308. https://doi.org/10.1007/s00500-016-2114-1

Simulation-driven modeling and optimization: ASDOM, Reykjavik, August 2014

Koziel, S., Leifsson, L. and Yang, X. (ed.) 2016. Simulation-driven modeling and optimization: ASDOM, Reykjavik, August 2014. Springer International Publishing.

A novel approach for multispectral satellite image classification based on the bat algorithm

Senthilnath, J., Kulkarni, S., Benediktsson, J. and Yang, X. 2016. A novel approach for multispectral satellite image classification based on the bat algorithm. IEEE Geoscience and Remote Sensing Letters. 13 (4), pp. 599-603. https://doi.org/10.1109/LGRS.2016.2530724

Stochastic decision-making in waste management using a firefly algorithm-driven simulation-optimization approach for generating alternatives

Imanirad, R., Yang, X. and Yeomans, J. 2016. Stochastic decision-making in waste management using a firefly algorithm-driven simulation-optimization approach for generating alternatives. in: Koziel, S., Leifsson, L. and Yang, X. (ed.) Simulation-Driven Modeling and Optimization: ASDOM, Reykjavik, August 2014 Switzerland Springer.

Stochastic decision-making in waste management using a firefly algorithm-driven simulation-optimization approach for generating alternatives

Imanirad, R., Yang, X. and Yeomans, J. 2016. Stochastic decision-making in waste management using a firefly algorithm-driven simulation-optimization approach for generating alternatives. in: Koziel, S., Leifsson, L. and Yang, X. (ed.) Simulation-Driven Modeling and Optimization: ASDOM, Reykjavik, August 2014 Springer.

Economic dispatch using chaotic bat algorithm

Adarsh, B., Raghunathan, T., Jayabarathi, T. and Yang, X. 2016. Economic dispatch using chaotic bat algorithm. Energy. 96, pp. 666-675. https://doi.org/10.1016/j.energy.2015.12.096

Review and applications of metaheuristic algorithms in civil engineering

Yang, X., Bekdaş, G. and Nigdeli, S. 2016. Review and applications of metaheuristic algorithms in civil engineering. in: Metaheuristics and Optimization in Civil Engineering Springer.

Application of the flower pollination algorithm in structural engineering

Nigdeli, S., Bekdaş, G. and Yang, X. 2016. Application of the flower pollination algorithm in structural engineering. in: Metaheuristics and Optimization in Civil Engineering Springer.

Lévy flight artificial bee colony algorithm

Sharma, H., Bansal, J., Arya, K. and Yang, X. 2016. Lévy flight artificial bee colony algorithm. International Journal of Systems Science. 47 (11), pp. 2652-2670. https://doi.org/10.1080/00207721.2015.1010748

An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems

Osaba, E., Yang, X., Diaz, F., Lopez-Garcia, P. and Carballedo, R. 2016. An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems. Engineering Applications of Artificial Intelligence. 48, pp. 59-71. https://doi.org/10.1016/j.engappai.2015.10.006

Multi-robot cooperative tasks using combined nature-inspired techniques

Palmieri, N., De Rango, F., Yang, X. and Marano, S. 2015. Multi-robot cooperative tasks using combined nature-inspired techniques. ECTA 2015: 7th International Conference on Evolutionary Computation Theory and Applications (part of IJCCI, the 7th International Joint Conference on Computational Intelligence). Lisbon, Portugal 12 - 14 Nov 2015 SciTePress. pp. 74-82 https://doi.org/10.5220/0005596200740082

A heuristic optimization method inspired by wolf preying behavior

Fong, S., Deb, S. and Yang, X. 2015. A heuristic optimization method inspired by wolf preying behavior. Neural Computing and Applications. 26 (7), pp. 1725-1738. https://doi.org/10.1007/s00521-015-1836-9

Sizing optimization of truss structures using flower pollination algorithm

Bekdaş, G., Nigdeli, S. and Yang, X. 2015. Sizing optimization of truss structures using flower pollination algorithm. Applied Soft Computing. 37, pp. 322-331. https://doi.org/10.1016/j.asoc.2015.08.037

Bio-inspired exploring and recruiting tasks in a team of distributed robots over mined regions

De Rango, F., Palmieri, N., Yang, X. and Marano, S. 2015. Bio-inspired exploring and recruiting tasks in a team of distributed robots over mined regions. SPECTS 2015 : International Symposium on Performance Evaluation of Computer and Telecommunication Systems. Chicago, IL, USA 26 - 29 Jul 2015 Institute of Electrical and Electronics Engineers (IEEE). pp. 1-8

Navigability analysis of magnetic map with projecting pursuit-based selection method by using firefly algorithm

Ma, Y., Zhao, Y., Wu, L., He, Y. and Yang, X. 2015. Navigability analysis of magnetic map with projecting pursuit-based selection method by using firefly algorithm. Neurocomputing. 159, pp. 288-297. https://doi.org/10.1016/j.neucom.2015.01.028

A biologically inspired network design model

Zhang, X., Adamatzky, A., Chan, F., Deng, Y., Yang, H., Yang, X., Tsompanas, M., Sirakoulis, G. and Mahadevan, S. 2015. A biologically inspired network design model. Scientific Reports. 5. https://doi.org/10.1038/srep10794

Modified bat algorithm with quaternion representation

Fister, I., Brest, J., Fister, I. and Yang, X. 2015. Modified bat algorithm with quaternion representation. IEEE Congress on Evolutionary Computation (CEC 2015). Sendai, Japan 25 - 28 May 2015 Institute of Electrical and Electronics Engineers (IEEE). pp. 491-498 https://doi.org/10.1109/CEC.2015.7256930

Nature-inspired algorithms: success and challenges

Yang, X. 2015. Nature-inspired algorithms: success and challenges. in: Engineering and Applied Sciences Optimization Springer.

Attraction and diffusion in nature-inspired optimization algorithms

Yang, X., Deb, S., Hanne, T. and He, X. 2015. Attraction and diffusion in nature-inspired optimization algorithms. Neural Computing and Applications. https://doi.org/10.1007/s00521-015-1925-9

Optimum design of frame structures using the eagle strategy with differential evolution

Talatahari, S., Gandomi, A., Yang, X. and Deb, S. 2015. Optimum design of frame structures using the eagle strategy with differential evolution. Engineering Structures. 91, pp. 16-25. https://doi.org/10.1016/j.engstruct.2015.02.026

Color image segmentation by cuckoo search

Nandy, S., Yang, X., Sarkar, P. and Das, A. 2015. Color image segmentation by cuckoo search. Intelligent Automation & Soft Computing: An International Journal . 21 (4), pp. 673-685. https://doi.org/10.1080/10798587.2015.1025480

Random-key cuckoo search for the travelling salesman problem

Ouaarab, A., Ahiod, B. and Yang, X. 2015. Random-key cuckoo search for the travelling salesman problem. Soft Computing. 19 (4), pp. 1099-1106. https://doi.org/10.1007/s00500-014-1322-9

Solutions of non-smooth economic dispatch problems by swarm intelligence

Hosseini, S., Yang, X., Gandomi, A. and Nemati, A. 2015. Solutions of non-smooth economic dispatch problems by swarm intelligence. in: Adaptation and Hybridization in Computational Intelligence Springer.

Bio-inspired computation in telecommunications

Yang, X., Chien, S. and Ting, T. (ed.) 2015. Bio-inspired computation in telecommunications. Morgan Kaufmann.

A short discussion about “Economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm”

Fister, I., Fister, I. and Yang, X. 2015. A short discussion about “Economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm”. Applied Thermal Engineering. 76, pp. 535-537. https://doi.org/10.1016/j.applthermaleng.2014.11.009

A short discussion about economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm

Fister, I., Fister, I. and Yang, X. 2015. A short discussion about economic optimization design of shell-and-tube heat exchangers by a cuckoo-search-algorithm. Applied Thermal Engineering. 76, pp. 535-537. https://doi.org/10.1016/j.applthermaleng.2014.11.009

Planning the sports training sessions with the bat algorithm

Fister, I., Rauter, S., Yang, X., Ljubič, K. and Fister, I. 2015. Planning the sports training sessions with the bat algorithm. Neurocomputing. 149, pp. 993-1002. https://doi.org/10.1016/j.neucom.2014.07.034

Introduction to computational mathematics

Yang, X. 2015. Introduction to computational mathematics. Singapore World Scientific Publishing.

Binary flower pollination algorithm and its application to feature selection

Rodrigues, D., Yang, X., De Souza, A. and Papa, J. 2015. Binary flower pollination algorithm and its application to feature selection. in: Yang, X. (ed.) Recent advances in swarm intelligence and evolutionary computation Springer.

Discrete Cuckoo search applied to job shop scheduling problem

Ouaarab, A., Ahiod, B. and Yang, X. 2015. Discrete Cuckoo search applied to job shop scheduling problem. in: Yang, X. (ed.) Recent advances in swarm intelligence and evolutionary computation Springer.

Swarm intelligence and evolutionary computation: overview and analysis

Yang, X. and He, X. 2015. Swarm intelligence and evolutionary computation: overview and analysis. in: Yang, X. (ed.) Recent advances in swarm intelligence and evolutionary computation Springer.

Recent advances in swarm intelligence and evolutionary computation

Yang, X. (ed.) 2015. Recent advances in swarm intelligence and evolutionary computation. Hendelberg, Berlin Springer.

Adaptation and hybridization in nature-inspired algorithms

Fister, I., Strnad, D., Yang, X. and Fister, I. 2015. Adaptation and hybridization in nature-inspired algorithms. in: Fister, I. and Fister, I. (ed.) Adaptation and Hybridization in Computational Intelligence Springer.

Solutions of non-smooth economic dispatch problems by swarm intelligence

Hosseini, S., Yang, X., Gandomi, A. and Nemati, A. 2015. Solutions of non-smooth economic dispatch problems by swarm intelligence. in: Fister, I. and Fister, I. (ed.) Adaptation and Hybridization in Computational Intelligence Springer.

Analysis of randomisation methods in swarm intelligence

Fister, I., Yang, X., Brest, J., Fister, D. and Fister, I. 2015. Analysis of randomisation methods in swarm intelligence. International Journal of Bio-Inspired Computation. 7 (1), pp. 36-49. https://doi.org/10.1504/IJBIC.2015.067989

Computational intelligence and metaheuristic algorithms with applications

Yang, X., Chien, S. and Ting, T. 2014. Computational intelligence and metaheuristic algorithms with applications. The Scientific World Journal. 2014, pp. 1-4. https://doi.org/10.1155/2014/425853

Synthesizing cross-ambiguity functions using the improved bat algorithm

Jamil, M., Zepernick, H. and Yang, X. 2014. Synthesizing cross-ambiguity functions using the improved bat algorithm. in: Recent Advances in Swarm Intelligence and Evolutionary Computation Springer.

Solving computationally expensive engineering problems: methods and applications

Koziel, S., Leifsson, L. and Yang, X. (ed.) 2014. Solving computationally expensive engineering problems: methods and applications. New York Springer International Publishing.

Advances of swarm intelligent systems in gene expression data classification

Talatahari, E., Talatahari, S., Gandomi, A. and Yang, X. 2014. Advances of swarm intelligent systems in gene expression data classification. Journal of Multiple-Valued Logic and Soft Computing. 22 (3), pp. 307-315.

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.

A novel improved accelerated particle swarm optimization algorithm for global numerical optimization

Wang, G., Hossein Gandomi, A., Yang, X. and Hossein Alavi, A. 2014. A novel improved accelerated particle swarm optimization algorithm for global numerical optimization. Engineering Computations. 31 (7), pp. 1198-1220. https://doi.org/10.1108/EC-10-2012-0232

Large-scale global optimization via swarm intelligence

Cheng, S., Ting, T. and Yang, X. 2014. Large-scale global optimization via swarm intelligence. in: Solving Computationally Expensive Engineering Problems Springer.

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

Mathematical analysis of energy efficiency optimality in multi-user OFDM systems

Chien, S., Ting, T., Yang, X. and Takahashi, K. 2014. Mathematical analysis of energy efficiency optimality in multi-user OFDM systems. Wireless Communications and Mobile Computing. 16 (3), pp. 252-263. https://doi.org/10.1002/wcm.2516

Analysis of firefly algorithms and automatic parameter tuning

Yang, X. 2014. Analysis of firefly algorithms and automatic parameter tuning. in: Emerging Research on Swarm Intelligence and Algorithm Optimization Information Science Reference, IGI-Global. pp. 36-49

Analysis of quality-of-service aware orthogonal frequency division multiple access system considering energy efficiency

Ting, T., Yang, X., Lee, S. and Chien, S. 2014. Analysis of quality-of-service aware orthogonal frequency division multiple access system considering energy efficiency. IET Communications. 8 (11), pp. 1947-1954. https://doi.org/10.1049/iet-com.2013.1161

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

Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan

Marichelvam, M., Prabaharan, T. and Yang, X. 2014. Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan. Applied Soft Computing. 19, pp. 93-101. https://doi.org/10.1016/j.asoc.2014.02.005

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

Nature-inspired optimization algorithms

Yang, X. 2014. Nature-inspired optimization algorithms. Elsevier.

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

Mathematical modelling and parameter optimization of pulsating heat pipes

Yang, X., Karamanoglu, M., Luan, T. and Koziel, S. 2014. Mathematical modelling and parameter optimization of pulsating heat pipes. Journal of Computational Science. 5 (2), pp. 119-125. https://doi.org/10.1016/j.jocs.2013.12.003

Hybrid metaheuristic algorithms: past, present, and future

Ting, T., Yang, X., Cheng, S. and Huang, K. 2014. Hybrid metaheuristic algorithms: past, present, and future. in: Recent Advances in Swarm Intelligence and Evolutionary Computation Springer.

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

Non-dominated sorting cuckoo search for multiobjective optimization

He, X., Li, N. and Yang, X. 2014. Non-dominated sorting cuckoo search for multiobjective optimization. 2014 IEEE Symposium on Swarm Intelligence (SIS). Orlando, Florida 09 - 12 Dec 2014 pp. 1-7 https://doi.org/10.1109/SIS.2014.7011772

Computational optimization, modelling and simulation: past, present and future

Yang, X., Koziel, S. and Leifsson, L. 2014. Computational optimization, modelling and simulation: past, present and future. Procedia Computer Science. 29, pp. 754-758. https://doi.org/10.1016/j.procs.2014.05.067

Discrete cuckoo search algorithm for job shop scheduling problem

Ouaarab, A., Ahiod, B., Yang, X. and Abbad, M. 2014. Discrete cuckoo search algorithm for job shop scheduling problem. 2014 IEEE International Symposium on Intelligent Control (ISIC). France 08 - 10 Oct 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 1872-1876 https://doi.org/10.1109/ISIC.2014.6967636

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

Feature selection in life science classification: metaheuristic swarm search

Fong, S., Deb, S., Yang, X. and Li, J. 2014. Feature selection in life science classification: metaheuristic swarm search. IT Professional. 16 (4), pp. 24-29. https://doi.org/10.1109/MITP.2014.50

Diversity and mechanisms in swarm intelligence

Yang, X. 2014. Diversity and mechanisms in swarm intelligence. International Journal of Swarm Intelligence Research. 5 (2), pp. 1-12. https://doi.org/10.4018/ijsir.2014040101

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

Swarm intelligence based algorithms: a critical analysis

Yang, X. 2014. Swarm intelligence based algorithms: a critical analysis. Evolutionary Intelligence. 7 (1), pp. 17-28. https://doi.org/10.1007/s12065-013-0102-2

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

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

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

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

Cuckoo search and firefly algorithm: overview and analysis

Yang, X. 2013. Cuckoo search and firefly algorithm: overview and analysis. in: Cuckoo Search and Firefly Algorithm Springer.

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

Flower pollination algorithm: a novel approach for multiobjective optimization

Yang, X., Karamanoglu, M. and He, X. 2014. Flower pollination algorithm: a novel approach for multiobjective optimization. Engineering Optimization. 46 (9), pp. 1222-1237. https://doi.org/10.1080/0305215X.2013.832237

A literature survey of benchmark functions for global optimisation problems

Jamil, M. and Yang, X. 2013. A literature survey of benchmark functions for global optimisation problems. International Journal of Mathematical Modelling and Numerical Optimisation. 4 (2), pp. 150-194. https://doi.org/10.1504/IJMMNO.2013.055204

Rare events forecasting using a residual-feedback GMDH neural network

Fong, S., Nannan, Z., Wong, R. and Yang, X. 2012. Rare events forecasting using a residual-feedback GMDH neural network. in: Seventh International Conference on Digital Information Management (ICDIM), 2012 IEEE Conference Publications. pp. 464-473

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

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

Swarm intelligence and bio-inspired computation: theory and applications

Yang, X., Cui, Z., Xiao, R., Gandomi, A. and Karamanoglu, M. (ed.) 2013. Swarm intelligence and bio-inspired computation: theory and applications. Elsevier.

Wolf search algorithm with ephemeral memory

Rui, T., Fong, S., Yang, X. and Deb, S. 2012. Wolf search algorithm with ephemeral memory. in: Seventh International Conference on Digital Information Management (ICDIM), 2012 IEEE Conference Publications. pp. 165 -172

Bat algorithm for topology optimization in microelectronic applications

Yang, X., Karamanoglu, M. and Fong, S. 2012. Bat algorithm for topology optimization in microelectronic applications. 1st International Conference on Future Generation Communication Technology. London, UK 12 - 14 Dec 2012 IEEE. pp. 150-155 https://doi.org/10.1109/FGCT.2012.6476566

Metaheuristic applications in structures and infrastructures

Gandom, A., Yang, X., Talatahari, S. and Alavi, A. 2013. Metaheuristic applications in structures and infrastructures. Elsevier.

Optimal test sequence generation using firefly algorithm

Srivatsava, P., Mallikarjun, B. and Yang, X. 2013. Optimal test sequence generation using firefly algorithm. Swarm and Evolutionary Computation. 8, pp. 44-53. https://doi.org/10.1016/j.swevo.2012.08.003

Oil supply between OPEC and non-OPEC based on game theory

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

Cuckoo search for business optimization applications

Yang, X., Deb, S., Karamanoglu, M. and He, X. 2012. Cuckoo search for business optimization applications. National Conference on Computing and Communication Systems (NCCCS). Durgapur, West Bengal, India 21 - 22 Nov 2012 IEEE. https://doi.org/10.1109/NCCCS.2012.6412973

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

Mathematical modeling with multidisciplinary applications

Yang, X. (ed.) 2013. Mathematical modeling with multidisciplinary applications. John Wiley & Sons.

Random walks, Lévy flights, Markov chains and metaheuristic optimization

Yang, X., Ting, T. and Karamanoglu, M. 2013. Random walks, Lévy flights, Markov chains and metaheuristic optimization. in: Future information communication technology and applications: ICFICE 2013 Springer Netherlands.

Artificial intelligence, evolutionary computing and metaheuristics : in the footsteps of Alan Turing

Yang, X. (ed.) 2013. Artificial intelligence, evolutionary computing and metaheuristics : in the footsteps of Alan Turing. Springer.

Multi-objective flower algorithm for optimization

Yang, X., Karamanoglu, M. and He, X. 2013. Multi-objective flower algorithm for optimization. 2013 International Conference on Computational Science . Barcelona, Spain. 05 - 07 Jun 2013 Elsevier. pp. 861- 868 https://doi.org/10.1016/j.procs.2013.05.251

Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems

Gandomi, A., Yang, X. and Alavi, A. 2013. Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with Computers. 29 (1), pp. 17-35. https://doi.org/10.1007/s00366-011-0241-y

Firefly algorithms for multimodal optimization

Yang, X. 2009. Firefly algorithms for multimodal optimization. in: Stochastic Algorithms: Foundations and Applications; 5th International Symposium, SAGA 2009, Sapporo, Japan, October 26-28, 2009. Proceedings Springer.

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.

Multiobjective cuckoo search for design optimization

Yang, X. and Deb, S. 2011. Multiobjective cuckoo search for design optimization. Computers & Operations Research. 40 (6), pp. 1616-1624. https://doi.org/10.1016/j.cor.2011.09.026

Metaheuristics in water, geotechnical and transport engineering

Yang, X., Gandomi, A., Talatahari, S. and Alavi, A. 2012. Metaheuristics in water, geotechnical and transport engineering. Elsevier.

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

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

Multiobjective firefly algorithm for continuous optimization

Yang, X. 2012. Multiobjective firefly algorithm for continuous optimization. Engineering with Computers.

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

Flower pollination algorithm for global optimization

Yang, X. 2012. Flower pollination algorithm for global optimization. in: Unconventional Computation and Natural Computation: 11th International Conference, UCNC 2012, Orléan, France, September 3-7, 2012. Proceedings Berlin Springer.

Bat algorithm for constrained optimization tasks, neural computing & applications

Gandomi, A., Yang, X., Alavi, A. and Talatahari, S. 2012. Bat algorithm for constrained optimization tasks, neural computing & applications. Neural Computing and Applications. https://doi.org/10.1007/s00521-012-1028-9

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

Yang, X., Koziel, S. and Leifsson, L. 2012. Computational optimization, modelling and simulation: smart algorithms and better models. Procedia Computer Science. 9, pp. 852-856. https://doi.org/10.1016/j.procs.2012.04.091

Bat algorithm: a novel approach for global engineering optimization

Yang, X. and Gandomi, A. 2012. Bat algorithm: a novel approach for global engineering optimization. Engineering Computations. 29 (5), pp. 464-483. https://doi.org/10.1108/02644401211235834

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

Coupled eagle strategy and differential evolution for unconstrained and constrained global optimization

Gandomi, A., Yang, X., Talatahari, S. and Deb, S. 2012. Coupled eagle strategy and differential evolution for unconstrained and constrained global optimization. Computers and Mathematics with Applications. 63 (1), pp. 191-200. https://doi.org/10.1016/j.camwa.2011.11.010

Mixed variable structural optimization using firefly algorithm

Gandomi, A., Yang, X. and Alavi, A. 2011. Mixed variable structural optimization using firefly algorithm. Computers & Structures. 89 (23-24), pp. 2325-2336. https://doi.org/10.1016/j.compstruc.2011.08.002

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

Yang, X., Deb, S. and Fong, S. 2011. Accelerated particle swarm optimization and support vector machine for business optimization and applications. in: Networked Digital Technologies : Third International Conference, NDT 2011, Macau, China, July 11-13, 2011. Proceedings Springer.

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.

Bat algorithm for multi-objective optimisation

Yang, X. 2011. Bat algorithm for multi-objective optimisation. International Journal of Bio-Inspired Computation (IJBIC). 3 (5), pp. 267-274. https://doi.org/10.1504/IJBIC.2011.042259

Computational optimization and applications in engineering and industry

Yang, X. and Koziel, S. (ed.) 2011. Computational optimization and applications in engineering and industry. Berlin Springer.

Computational optimization, methods and algorithms

Koziel, S. and Yang, X. (ed.) 2011. Computational optimization, methods and algorithms. Berlin Springer.

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

Engineering optimization: an introduction with metaheuristic applications

Yang, X. 2010. Engineering optimization: an introduction with metaheuristic applications. New Jersey John Wiley & Sons.

Optimization and data mining for fracture prediction in geoscience

Shi, G. and Yang, X. 2010. Optimization and data mining for fracture prediction in geoscience. 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

A new metaheuristic bat-inspired algorithm

Yang, X. 2010. A new metaheuristic bat-inspired algorithm. in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) Berlin Springer.

Eagle strategy using Lévy walk and firefly algorithm for stochastic optimization

Yang, X. and Deb, S. 2010. Eagle strategy using Lévy walk and firefly algorithm for stochastic optimization. in: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) Springer.

Engineering optimisation by cuckoo search

Yang, X. and Deb, S. 2010. Engineering optimisation by cuckoo search. International Journal of Mathematical Modelling and Numerical Optimisation. 1 (4), pp. 330 -343. https://doi.org/10.1504/IJMMNO.2010.03543

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
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