Real-world Application of Bio-inspired Metaheuristics

 

Dr. Andrew Lewis, Griffith University, Australia

Dr. Andrew Lewis, Griffith University, Australia

Dr. Andrew Lewis is a Senior Research Specialist in eResearch Services and an Adjunct Senior Lecturer in ICT at Griffith University. Prior to this appointment he worked in industrial applied research with BHP Billiton. His research interests include: parallel optimisation algorithms for large numerical simulations, including evolutionary programming, particle swarm and ant colony systems, multi-objective optimisation techniques for engineering design, and parallel, distributed and grid computing methods. He has numerous publications in computational optimisation.

 

drmarcusrandall

Dr. Marcus Randall, Bond University, Australia

Associate Professor Marcus Randall obtained his doctorate from Griffith University in applied mathematics and has worked at Bond University since 1998. He is a computer scientist with research interests in combinatorial optimisation, heuristics, search algorithms and high performance computing. Marcus has also published around 70 works, including a number of books, chapters for books, journals and conferences articles dealing with combinatorial optimisation, meta-heuristic search techniques and parallel processing/programming.

 

Dr Lewis and Dr Randall are co-authors of several book chapters, journal and conference papers in metaheuristic search and optimisation, and together are co-editors of a volume of contributed works on bio-inspired optimisation methods and applications.


In many industries and applications the use of computational models is now routine practice. In the engineering design process and scientific research, they are often used to find the best of a number of solutions as measured against one or more objectives. In recent decades this has led to a growing demand for tools that enable rigorous and systematic exploration of the model parameter space. The first methods applied drew on experience in classical, mathematical methods, but these were soon joined by a rapidly increasing repertoire of metaheuristic methods. By the early 1960’s, inspiration for these methods was being drawn from biological processes, with the introduction of evolutionary strategies and evolutionary programming, followed by the widely successful application of genetic algorithms. More recently, new innovations modelled on ant colonies, swarming behaviour in insects and animals, artificial immune systems, and further developments such as differential evolution and extremal optimisation have started to find application to a variety of problems.


In the transition from theory to practice, a variety of challenges may arise. Great care may need to be taken in problem formulation, and considerable effort expended in adapting methods to the needs of, for example, problems of high dimensionality, multi-­‐ and many objectives, and complex fitness landscapes. As these computational methods begin to be applied to difficult problems in molecular chemistry, radio frequency design and bioinformatics, to name a few, novel ideas are needed to adapt and enhance their performance.


This special session will seek to present a selection of contributed papers describing the application of bio-­‐inspired metaheuristics to real problems of industrial and scientific research and development. In particular, applications that illustrate the means taken for practical application to challenging problems are of particular interest. It is planned that the session will allow not only presentation of these papers but also extended time for their discussion to promote interchange of innovative ideas between participants.