Walking Fish Group:
applying & improving evolutionary technology
EVOLUTIONARY ALGORITHMS IN INDUSTRY
Many problems faced by companies are impractical to solve by traditional analytical methods. Such problems may be computationally intractable, or may involve highly non-linear, complex systems. These difficulties offer no impediment to evolutionary algorithms. An evolutionary algorithm requires only a procedure for evaluating the quality (or "fitness") of a proposed solution - the search for good solutions then follows from the structure of the algorithm.
Evolutionary algorithms have a number of features that make them especially well suited to complex real-world problems. For example, evolutionary algorithms can easily be adapted to different instances of a problem (for example fine-tuning an existing design vs green fields exploration of new designs); they are inherently parallel in nature; and they can handle multiple (even conflicting) objectives in a very natural way.
The academic literature is littered with examples of the successful application of evolutionary algorithms to real world problems, including the optimisation of two-phase jet nozzle design, the design of heat exhanger networks, nuclear reactor design, chemical plant design, the design of water distribution systems, load cell shape optimisation, and aircraft design.
More recently, WFG itself has identified the benefits of applying evolutionary algorithm optimisation techniques to problems in the mining industry. For more information on WFG's activities, or for contact information, use the site navigation bar on the right.
ABOUT THE WALKING FISH GROUP
The Walking Fish Group (WFG) was formed in 2001 to address the needs of industry partners by adapting modern optimisation techniques, specifically evolutionary algorithms, to their needs. The group has since branched out to work on the technology underpinning evolutionary algorithms.
ABOUT THIS SITE
The layout for this site was based on the Box Lessons Tutorial, with a number of changes to the source in particular. Originally created by Simon Huband.
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