Cloud computing provides convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. In the same time, services computing is becoming more and more prominent in the Internet environment with the rapid growth of services available on the internet. This raises issues for service providers such as, service deployment, Web service composition and service location allocation, resource allocation and scheduling, etc. Furthermore, there are multiple potentially conflicting objectives (called Quality-of-Service, QoS) to be considered simultaneously in the problem such as response time, cost, reliability, safety, etc. In the era of cloud computing and Big Data, the number and complexity of Web services on the Internet is increasing rapidly. Traditional service composition approaches have come to a performance bottleneck.

Evolutionary computation (EC) has been successfully applied to many challenging real-world problems. This special session aims to solve the service-oriented computing problems with EC techniques, covering all different evolutionary computation paradigms such as Genetic Algorithms (GAs), Genetic Programming (GP), Evolutionary Programming (EP), Evolution Strategies (ES), Memetic Algorithms (MAs), Learning Classifier Systems (LCS), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Differential Evolution (DE), and Evolutionary Multi-objective Optimization (EMO).

The scope of this special session includes both new theories and methods on how to solve the challenging services computing and cloud computing problems such as Web service composition, workflow scheduling and resource allocation in clouds, and service location allocation more effectively and efficiently. Authors are invited to submit their original and unpublished work to this special session.

Topics of interest include, but not limited to:

• Evolutionary Web service composition
• Evolutionary Web service workflow optimisation
• Evolutionary Web service selection
• Evolutionary Web service location allocation
• Evolutionary Web service scheduling
• Evolutionary semantic Web service composition
• Evolutionary dynamic Web service composition
• Multi-objective Web service composition
• Evolutionary computation for resource allocation in Cloud
• Evolutionary computation for workflow scheduling in Cloud
• Evolutionary computation for distributed Web service composition
• Evolutionary computation for smart homes and smart cities
  • Novel representations and search operators for Service-oriented computing
  • Cooperative coevolution for Service-oriented computing
  • Neural networks for service-oriented computing
  • Fuzzy systems for service-oriented computing
  • Evolutionary computation for Big Data As A Service
  • Evolutionary computation for Internet of Things Services
  • Hybrid algorithms between EC, neural networks and fuzzy systems for service-oriented computing

Submission Guideline:

Papers for IEEE CEC 2021 should be submitted electronically through the Congress website at http://cec2021.mini.pw.edu.pl by January 31, 2021. Special session papers are treated the same as regular conference papers. Please specify that your paper is for the Special Session on Evolutionary Computation for Service-Oriented Computing. All papers accepted and presented at CEC2021 will be included in the conference proceedings published by IEEE Explore, which are typically indexed by EI.

Important Dates:

• 31 January 2021: Deadline for submission of full papers
• 22 March 2021: Notification of acceptance
• 7 April 2021: Deadline for Final paper submission
• 28 June - 1 July 2021: Conference Dates

Special Session Organizers:

• Dr. Hui Ma, Victoria University of Wellington, New Zealand (hui.ma@ecs.vuw.ac.nz)
• Dr. Yi Mei, Victoria University of Wellington, New Zealand (yi.mei@ecs.vuw.ac.nz)
• Prof. Mengjie Zhang, Victoria University of Wellington, New Zealand (Mengjie.Zhang@ecs.vuw.ac.nz)

Program Committee (TBA)