Research

Joshua Knowles
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Research interests:

  • Evolutionary computation
  • Multiobjective optimization
  • Systems biology and bioinformatics applications of the above

Projects, past and present:

  • Multiobjective optimization of expensive functions using landscape approximation: ParEGO
  • Evolutionary multiobjective clustering algorithms, MOCK and VIENNA
  • The multiobjective quadratic assignment problem (mQAP)
  • The Pareto Archived Evolution Strategy, PAES
  • M-PAES, a memetic algorithm for multiobjective optimization
  • Bounded Pareto archives: theory and algorithms
  • Performance assessment of multiobjective optimization algorithms
  • Multiobjectivization: decomposition of single-objective problems by reformulating them with multiple criteria.
  • Semi-supervised classification and transductive inference.

Joshua D. Knowles