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  • Jing W, Xue Y and Wang J. (2023). An Enhanced Energy-Efficient Web Service Composition Algorithm Based on the Firefly Algorithm. Journal of Database Management. 34:1. (1-19). Online publication date: 21-Apr-2023.

    https://doi.org/10.4018/JDM.321740

  • Zhu M, Yu F, Yan X, Li J and Wang Y. (2021). Scaling up Mobile Service Selection in Edge Computing Environment with Cuckoo Optimization Algorithm 2021 IEEE International Conference on Services Computing (SCC). 10.1109/SCC53864.2021.00056. 978-1-6654-1683-2. (394-400).

    https://ieeexplore.ieee.org/document/9592510/

  • Masdari M, Nozad Bonab M and Ozdemir S. (2021). QoS-driven metaheuristic service composition schemes: a comprehensive overview. Artificial Intelligence Review. 54:5. (3749-3816). Online publication date: 1-Jun-2021.

    https://doi.org/10.1007/s10462-020-09940-4

  • Gorski T and Wozniak A. Optimization of Business Process Execution in Services Architecture: A Systematic Literature Review. IEEE Access. 10.1109/ACCESS.2021.3102668. 9. (111833-111852).

    https://ieeexplore.ieee.org/document/9507503/

  • Purohit L and Kumar S. (2020). A study on evolutionary computing based web service selection techniques. Artificial Intelligence Review. 10.1007/s10462-020-09872-z.

    http://link.springer.com/10.1007/s10462-020-09872-z

  • da Silva A, Ma H, Mei Y and Zhang M. A Survey of Evolutionary Computation for Web Service Composition: A Technical Perspective. IEEE Transactions on Emerging Topics in Computational Intelligence. 10.1109/TETCI.2020.2969213. 4:4. (538-554).

    https://ieeexplore.ieee.org/document/8984706/

  • Zhao X, Li R and Zuo X. (2019). Advances on QoS‐aware web service selection and composition with nature‐inspired computing. CAAI Transactions on Intelligence Technology. 10.1049/trit.2019.0018. 4:3. (159-174). Online publication date: 1-Sep-2019.

    https://onlinelibrary.wiley.com/doi/10.1049/trit.2019.0018

  • Zhang W, Yang Y, Zhang S, Yu D and Chen Y. (2017). A new three-dimensional manufacturing service composition method under various structures using improved Flower Pollination Algorithm. Enterprise Information Systems. 10.1080/17517575.2017.1410895. 12:5. (620-637). Online publication date: 28-May-2018.

    https://www.tandfonline.com/doi/full/10.1080/17517575.2017.1410895

  • Guo X, Chen S, Zhang Y, Li W and Qi L. (2017). Service Composition Optimization Method Based on Parallel Particle Swarm Algorithm on Spark. Security and Communication Networks. 2017. Online publication date: 1-Jan-2017.

    https://doi.org/10.1155/2017/9097616

  • Mesquita C, Cavalca U, Pereira A and Carrano E. A traffic shaping optimization methodology for web systems. Proceedings of the 19th Brazilian symposium on Multimedia and the web. (209-216).

    https://doi.org/10.1145/2526188.2526190

  • Cavalca U, Mesquista C, Pereira A and Carrano E. (2013). A computational intelligence based approach for computer network traffic shaping 2013 IEEE Congress on Evolutionary Computation (CEC). 10.1109/CEC.2013.6557893. 978-1-4799-0454-9. (2680-2686).

    http://ieeexplore.ieee.org/document/6557893/

  • Suciu M, Pallez D, Cremene M and Dumitrescu D. Adaptive MOEA/D for QoS-based web service composition. Proceedings of the 13th European conference on Evolutionary Computation in Combinatorial Optimization. (73-84).

    https://doi.org/10.1007/978-3-642-37198-1_7

  • Cavalca U, Mesquista C, Pereira A and Carrano E. (2012). A methodology for traffic shaping multiobjective optimization for next generation network 2012 Fourth International Conference on Computational Aspects of Social Networks (CASoN). 10.1109/CASoN.2012.6412426. 978-1-4673-4794-5. (345-350).

    http://ieeexplore.ieee.org/document/6412426/

  • Pop C, Chifu V, Salomie I, Negrean A and Jeflea H. (2012). Hybrid genetic algorithm for selecting the optimal or near-optimal solution in semantic Web service composition 2012 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP). 10.1109/ICCP.2012.6356161. 978-1-4673-2952-1. (57-64).

    http://ieeexplore.ieee.org/document/6356161/