Grid Services for Multi-objective Optimisation

The emerging grid technology is defined as an infrastructure for secure and coordinated large-scale resource sharing. In this paper, we describe the architecture and grid services of DECGrid. DECGrid enables distributed design experts to collaborate and share resources during design optimisation. Mathematical models are built using services by experts. These models are then directly linked to NSGA-II optimisation algorithm service and allow design experts to enter design parameters of their choice. A real-life case study-welded beam problem was used to validate the prototype. The results obtained showed a wider spread in the solution space compared to the results in literature.

[1]  Simon J. Cox.  Proceedings of the UK e-science All Hands Meeting , 2007 .

[2]  Tomoyuki Hiroyasu,et al.  Optimization Problem Solving System using Grid RPC , 2003 .

[3]  Sotirios Chatzis,et al.  Managing service level agreement contracts in OGSA-based Grids , 2008, Future Gener. Comput. Syst..

[4]  John S. Gero,et al.  Computational Models of Creative Design Processes , 1994 .

[5]  Michael Sobolewski,et al.  Preliminary Design using Distributed Service-Based Computing , 2005 .

[6]  A. Senthil Kumar,et al.  Development of a distributed collaborative design framework within peer-to-peer environment , 2008, Comput. Aided Des..

[7]  Norman W. Paton,et al.  The design and implementation of Grid database services in OGSA‐DAI , 2005, Concurr. Pract. Exp..

[8]  Omer F. Rana,et al.  Towards Autonomous Evolutionary Design Systems via Grid-Based Technologies , 2005 .

[9]  Jim Austin,et al.  Delivering a Grid enabled Distributed Aircraft Maintenance Environment ( DAME ) , 2003 .

[10]  Anthony Rowe,et al.  The Design of Discovery Net: Towards Open Grid Services for Knowledge Discovery , 2003, Int. J. High Perform. Comput. Appl..

[11]  Ian T. Foster,et al.  The Anatomy of the Grid: Enabling Scalable Virtual Organizations , 2001, Int. J. High Perform. Comput. Appl..

[12]  Hong Liu,et al.  Supporting creative design in a visual evolutionary computing environment , 2004 .

[13]  Simon J. Cox,et al.  User Deployment of Grid Toolkits to Engineers , 2004 .

[14]  K. Deb.  An Efficient Constraint Handling Method for Genetic Algorithms , 2000 .

[15]  Terry Dartnall,et al.  Artificial Intelligence and Creativity , 1994 .

[16]  Carlos A. Coello Coello,et al.  Use of a self-adaptive penalty approach for engineering optimization problems , 2000 .