Abstract
Facing to the globalization and increasing competition of manufacturing enterprise, how to integrate the existent manufacturing services in cloud manufacturing model to form the newly value-added services in order to fulfill the user requirements has become a significant issue in manufacturing area. In this context, a discrete hybrid Bees Algorithm (DHBA) is proposed to solve service optimal the selection in resource service aggregation. The problem of service aggregation with QoS global optimal is transformed into a multi-objective services aggregation optimization with QoS constraints, and DHBA is utilized to produce a near-optimal solution. A case study together with a set of simulation experiment is presented and the results demonstrate the effectiveness and feasibility of the proposed method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Zhang, L., Luo, Y.L., Tao, F., Li, B.H., Ren, L., Zhang, X.S., Guo, H., Cheng, Y., Hu, A.R., Liu, Y.K.: Cloud manufacturing: A new manufacturing paradigm. In: Enterprise Information Systems, pp. 1–21 (2012)
Liu, S.L., Liu, Y.X., Zhang, F., Tang, G.F., Jing, N.: A dynamic web service selection algorithm with QoS global optimal in web services composition. Journal of Software 18(3), 646–656 (2007)
Tao, F., Zhao, D.M., Hu, Y.F., Zhou, Z.D.: Correlation-aware resource service composition and optimal-selection in manufacturing grid. European Journal of Operational Research 201(1), 129–143 (2010)
Arora, J.S.: Introduction to optimum design. Elsevier, New York (2004)
Pham, D.T., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S., Zaidi, M.: The bees algorithm. Technical Note, Manufacturing Engineering Centre, Cardiff University: Cardiff (2005)
Pham, D.T.: The bees algorithm: modelling foraging behaviour to solve continuous optimization problems. Proc. Inst. Mech. Eng. Part C: J. Mech. Eng. Sci. 233(12), 2919–2938 (2009)
Pham, D.T., Ghanbarzadeh, A.: Multi-objective optimisation using the bees algorithm. In: Innovative Production Machines and Systems Conference, IPROMS 2007 (2007)
Goksala, F.P., Karaoglanb, I., Altiparmak, F.: A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery. Computer & Industrial Engineering 65(1), 39–53 (2012)
Nagy, G., Salhi, S.: Heuristic algorithms for single and multiple depot vehicle routing problems with pickups and deliveries. European Journal of Operational Research 162(1), 126–141 (2005)
Zeng, L.Z., Benatallah, B., Ngu, A.H.H., Dumas, M., Kalagnanam, J., Chang, H.: QoS-aware middleware for Web services composition. IEEE Transactions on Software Engineering 30(5), 311–327 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tian, S., Liu, Q., Xu, W., Yan, J. (2013). A Discrete Hybrid Bees Algorithm for Service Aggregation Optimal Selection in Cloud Manufacturing. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2013. IDEAL 2013. Lecture Notes in Computer Science, vol 8206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41278-3_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-41278-3_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41277-6
Online ISBN: 978-3-642-41278-3
eBook Packages: Computer ScienceComputer Science (R0)