Welcome to the
Genetic Algorithms Research and Applications Group (GARAGe)

Bill Punch (punch@cse.msu.edu, 517-353-3541)
Erik Goodman (goodman@egr.msu.edu, 517-355-6453)

A Little About the GARAGe

The MSU Genetic Algorithms Research and Applications Group (the GARAGe) is a multi-disciplinary unit interested in the application of Genetic Algorithms and Genetic Programming to real-world problems, as well as fundamental research on GA and GP. We are doing or have recently done a number of interesting projects, both in terms of GA/GP fundamental research and in GA/GP applications, including:
  • research on sustainable and scalable evolutionary methods, resulting in development of the Hierarchical Fair Competition principle.  A patent for the Quick HFC algorithm is being pursued.
  • mathematical modeling,  by Bulent Buyukbozkirli, of genetic algorithm behavior, aimed at gaining insight useful for configuring genetic algorithms to solve particular problems
  • automated design, including research on composite material design and multi-objective design of automotive components for crashworthiness, weight savings, and other characteristics (see spinoff company, Red Cedar Technology)
  • automated design of mechatronic systems using bond graphs and genetic programming (NSF)
  • parallelization of GAs/GPs including use of hierarchical decomposition of problem domains and heterogeneous design spaces using concepts such as iiga, the injection island GA
  • nesting of irregular shapes using feature matching and GAs
  • multiple population topologies and interchange methodologies
  • mobile communications infrastructure optimization
  • scheduling applications, including job-shop scheduling
  • configuration applications, particularly physics applications of optimal molecule configurations for particular systems like C60 (buckyballs)
  • protein folding and protein/ligand docking
  • plant floor layout
  • and many others.

We have three main GA/GP faculty (Punch, Goodman, and Ofria) and 6 other faculty members collaborating on GA/GP applications. Charles Ofria, a new faculty member in Computer Science and Engineering, studies evolution using the AVIDA software for artificial life, which he developed with Chris Adami, now collaborating closely with Richard Lenski (a microbiologist and evolutionary biologist).  We currently have about 7 graduate students and 2 visiting professors and visiting scholars working on various projects, as well as established collaborations with researchers in the former Soviet Union and China.

Erik Goodman and colleague Ron Averill founded a company, Red Cedar Technology, building on their design automation experiences in the GARAGe and creating the HEEDS software, which combines evolutionary methods with many others.
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