General Upper Bounds on the Runtime of Parallel Evolutionary Algorithms*

  title={General Upper Bounds on the Runtime of Parallel Evolutionary Algorithms*},
  author={J{\"o}rg L{\"a}ssig and Dirk Sudholt},
  journal={Evolutionary Computation},
We present a general method for analyzing the runtime of parallel evolutionary algorithms with spatially structured populations. Based on the fitness-level method, it yields upper bounds on the expected parallel runtime. This allows for a rigorous estimate of the speedup gained by parallelization. Tailored results are given for common migration topologies: ring graphs, torus graphs, hypercubes, and the complete graph. Example applications for pseudo-Boolean optimization show that our method is… CONTINUE READING


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