Optimizing Service Selection Using Hybrid Multi-objective Genetic Algorithms
- https://doi.org/10.2991/icmmita-15.2015.26How to use a DOI?
- List the keywords covered in your paper. These keywords will also be used by the publisher to produce a keyword index. Optimizing Service Selection; Hybrid Multi-objective; Genetic Algorithms.
Developments in web services lead increasing numbers of enterprises to focus themselves on core business by outsourcing parts of service flows. As an important measure of the web service, quality of service (QoS), determines the success of the combined services to some extent, highlighting the need for service users and providers to reach an agreement on QoS of web services. This agreement is known as a Service-Level Agreement (SLA).A particular task may be performed by many services with the same functions but different QoS values.A method for automatically selecting the services is thus needed.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Bo Li AU - Changsheng Zhang AU - Baoxing Bai PY - 2015/11 DA - 2015/11 TI - Optimizing Service Selection Using Hybrid Multi-objective Genetic Algorithms BT - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications PB - Atlantis Press SP - 116 EP - 122 SN - 2352-538X UR - https://doi.org/10.2991/icmmita-15.2015.26 DO - https://doi.org/10.2991/icmmita-15.2015.26 ID - Li2015/11 ER -