A New Asynchronous Parallel Evolutionary Algorithm for Function Optimization

نویسندگان

  • Pu Liu
  • Francis C. M. Lau
  • Michael J. Lewis
  • Cho-Li Wang
چکیده

This paper introduces a new asynchronous parallel evolutionary algorithm (APEA) based on the island model for solving function optimization problems. Our fully distributed APEA overlaps the communication and computation efficiently and is inherently fault-tolerant in a large-scale distributed computing environment. For the scalable BUMP problem, our APEA algorithm achieves the best solution for the 50-dimension problem, and is the first algorithm of which we are aware that can solve the 1,000,000dimension problem. For other benchmark problems, our APEA finds the best solution to G7 in fewer time steps than [16,17], and finds a better solution to G10 than [17].

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تاریخ انتشار 2002