IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v55y2017i16p4765-4784.html
   My bibliography  Save this article

A hybrid approach combining modified artificial bee colony and cuckoo search algorithms for multi-objective cloud manufacturing service composition

Author

Listed:
  • Jiajun Zhou
  • Xifan Yao

Abstract

This paper proposes a multi-objective hybrid artificial bee colony (MOHABC) algorithm for service composition and optimal selection (SCOS) in cloud manufacturing, in which both the quality of service and the energy consumption are considered from the perspectives of economy and environment that are two pillars of sustainable manufacturing. The MOHABC uses the concept of Pareto dominance to direct the searching of a bee swarm, and maintains non-dominated solution found in an external archive. In order to achieve good distribution of solutions along the Pareto front, cuckoo search with Levy flight is introduced in the employed bee search to maintain diversity of population. Furthermore, to ensure the balance of exploitation and exploration capabilities for MOHABC, the comprehensive learning strategy is designed in the onlooker search so that every bee learns from the external archive elite, itself and other onlookers. Experiments are carried out to verify the effect of the improvement strategies and parameters’ impacts on the proposed algorithm and comparative study of the MOHABC with typical multi-objective algorithms for SCOS problems are addressed. The results show that the proposed approach obtains very promising solutions that significantly surpass the other considered algorithms.

Suggested Citation

  • Jiajun Zhou & Xifan Yao, 2017. "A hybrid approach combining modified artificial bee colony and cuckoo search algorithms for multi-objective cloud manufacturing service composition," International Journal of Production Research, Taylor & Francis Journals, vol. 55(16), pages 4765-4784, August.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:16:p:4765-4784
    DOI: 10.1080/00207543.2017.1292064
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2017.1292064
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2017.1292064?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alkın Yurtkuran & Erdal Emel, 2016. "A discrete artificial bee colony algorithm for single machine scheduling problems," International Journal of Production Research, Taylor & Francis Journals, vol. 54(22), pages 6860-6878, November.
    2. Rameshwar Dubey & Angappa Gunasekaran & Anindya Chakrabarty, 2015. "World-class sustainable manufacturing: framework and a performance measurement system," International Journal of Production Research, Taylor & Francis Journals, vol. 53(17), pages 5207-5223, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wei He & Guozhu Jia & Hengshan Zong & Tao Huang, 2019. "Multi-Objective Cloud Manufacturing Service Selection and Scheduling with Different Objective Priorities," Sustainability, MDPI, vol. 11(17), pages 1-24, September.
    2. Shuangyao Zhao & Qiang Zhang & Zhanglin Peng & Xiaonong Lu, 2020. "Personalized manufacturing service composition recommendation: combining combinatorial optimization and collaborative filtering," Journal of Combinatorial Optimization, Springer, vol. 40(3), pages 733-756, October.
    3. Juan Li & Qing An & Hong Lei & Qian Deng & Gai-Ge Wang, 2022. "Survey of Lévy Flight-Based Metaheuristics for Optimization," Mathematics, MDPI, vol. 10(15), pages 1-27, August.
    4. Haghnegahdar, Lida & Chen, Yu & Wang, Yong, 2022. "Enhancing dynamic energy network management using a multiagent cloud-fog structure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    5. Hongbin Wang & Yang Ding & Hanchuan Xu, 2024. "Particle swarm optimization service composition algorithm based on prior knowledge," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 35-53, January.
    6. Shuangyao Zhao & Qiang Zhang & Zhanglin Peng & Xiaonong Lu, 0. "Personalized manufacturing service composition recommendation: combining combinatorial optimization and collaborative filtering," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-24.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Blanka Tundys & Tomasz Wiśniewski, 2018. "The Selected Method and Tools for Performance Measurement in the Green Supply Chain—Survey Analysis in Poland," Sustainability, MDPI, vol. 10(2), pages 1-26, February.
    2. Harpreet Kaur & Surya Prakash Singh, 2019. "Sustainable procurement and logistics for disaster resilient supply chain," Annals of Operations Research, Springer, vol. 283(1), pages 309-354, December.
    3. Wang, Hui & Gong, Qiguo & Wang, Shouyang, 2017. "Information processing structures and decision making delays in MRP and JIT," International Journal of Production Economics, Elsevier, vol. 188(C), pages 41-49.
    4. Nisha Paul Kulangara & Markus Biehl & Edmund L. Prater, 2022. "Environmentally sustainable development initiatives in upstream strategic outsourcing relationships: Examining the role of innovative capabilities," Business Strategy and the Environment, Wiley Blackwell, vol. 31(7), pages 3014-3027, November.
    5. Ma-Lin Song & Ron Fisher & Jian-Lin Wang & Lian-Biao Cui, 2018. "Environmental performance evaluation with big data: theories and methods," Annals of Operations Research, Springer, vol. 270(1), pages 459-472, November.
    6. Cagatay Tasdemir & Rado Gazo, 2018. "A Systematic Literature Review for Better Understanding of Lean Driven Sustainability," Sustainability, MDPI, vol. 10(7), pages 1-54, July.
    7. Steven Day & Janet Godsell & Donato Masi & Wanrong Zhang, 2020. "Predicting consumer adoption of branded subscription services: A prospect theory perspective," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1310-1330, March.
    8. Monica Shukla & Ravi Shankar, 2022. "Modeling of critical success factors for adoption of smart manufacturing system in Indian SMEs: an integrated approach," OPSEARCH, Springer;Operational Research Society of India, vol. 59(4), pages 1271-1303, December.
    9. de Sousa Jabbour, Ana Beatriz Lopes & Jabbour, Charbel Jose Chiappetta & Foropon, Cyril & Godinho Filho, Moacir, 2018. "When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 18-25.
    10. Hongli Yu & Yuelin Gao & Le Wang & Jiangtao Meng, 2020. "A Hybrid Particle Swarm Optimization Algorithm Enhanced with Nonlinear Inertial Weight and Gaussian Mutation for Job Shop Scheduling Problems," Mathematics, MDPI, vol. 8(8), pages 1-17, August.
    11. Md. Mazharul Islam & Majed Alharthi, 2020. "Relationships among Ethical Commitment, Ethical Climate, Sustainable Procurement Practices, and SME Performance: An PLS-SEM Analysis," Sustainability, MDPI, vol. 12(23), pages 1-25, December.
    12. Benjamin T. Hazen & Diane A. Mollenkopf & Yacan Wang, 2017. "Remanufacturing for the Circular Economy: An Examination of Consumer Switching Behavior," Business Strategy and the Environment, Wiley Blackwell, vol. 26(4), pages 451-464, May.
    13. Hariyani, Dharmendra & Mishra, Sanjeev & Hariyani, Poonam & Sharma, Milind Kumar, 2023. "Drivers and motives for sustainable manufacturing system," Innovation and Green Development, Elsevier, vol. 2(1).
    14. Ardian Qorri & Saranda Gashi & Andrzej Kraslawski, 2021. "Performance outcomes of supply chain practices for sustainable development: A meta‐analysis of moderators," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(1), pages 194-216, January.
    15. Surabhi Verma & Som Sekhar Bhattacharyya, 2017. "Drivers and Inhibitors of Big Data as a Service Adoption in India," Emerging Economy Studies, International Management Institute, vol. 3(1), pages 68-85, May.
    16. Veronika Yu. Zemzyulina & Natalya R. Kelchevskaya & Ilia M. Chernenko, 2023. "The Impact of Sustainable Development and Reliability on the Performance of Russian Enterprises in the Context of an Economic Fragmentation," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 22(4), pages 1056-1086.
    17. Stephen Fox & Yusuf Mubarak & Abdurasak Adam, 2020. "Ecological Analyses of Social Sustainability for International Production with Fixed and Moveable Technologies," Sustainability, MDPI, vol. 12(20), pages 1-15, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:55:y:2017:i:16:p:4765-4784. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.