In engineering design and scientific research, computational models are often used to find the best solutions as measured against one or more objectives. There is a growing demand for tools that enable rigorous and systematic exploration of the model parameter space. In the transition from theory to practice, a variety of challenges may arise. Great care may need to be taken in problem formulation, algorithm selection and design, and in adapting methods to practical needs and available computing resources. The workshop will allow presentation of papers and an opportunity for their discussion to promote interchange of innovative ideas between participants.
This workshop invites papers discussing design and application of optimisation algorithms to real problems in computational science. Emphasis is placed on algorithms and methods that are particularly suited to parallel computing environments, such as Grids, Clusters, GPGPU and Cloud Computing, due to the practical needs of many of the target problems. Applications of particular interest are those that illustrate the means taken for practical application to challenging problems: for example, problems of high dimensionality, multi- and many objectives, and complex fitness landscapes. Also of interest are descriptions of optimisation frameworks, particularly those allowing interaction and visual analysis.
Topics for discussion include, but are not limited to:
- Optimisation theory and algorithms
- Visualisation for optimisation
- Interactive optimisation
- Real world applications
- Novel search heuristics
- Robust optimisation
- Design frameworks and optimisation
- Metamodels in engineering
- Manufacturing optimisation
- Multidisciplinary design methods
- Parallel coordinates in design optimisation
- Topology optimisation