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Status: Unchecked ×Keyword: Gaussian mutation ×Clear all

3 claims from 1 paper

1. Computer Science › Metaheuristic Optimization Algorithms Research

   Evolutionary programming made faster

   Yao, Liu and Lin · IEEE Transactions on Evolutionary Computation · 1999

   The paper proposes a fast evolutionary programming method using Cauchy mutation, compares it analytically and empirically with the classical Gaussian version, and then proposes an improved mixed-mutation method.

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   1. Unchecked“The paper shows that FEP is very good at search in a large neighborhood while CEP is better at search in a small local neighborhood.”
   2. UncheckedOn 23 benchmark problems, fast evolutionary programming beat the classical version on multimodal functions with many local minima and matched it on simpler ones.“For a suite of 23 benchmark problems, FEP performs much better than CEP for multimodal functions with many local minima while being comparable to CEP in performance for unimodal and multimodal functions with only a few local minima.”
   3. UncheckedAn improved fast evolutionary programming method (IFEP) did at least as well as the better of two earlier methods on most benchmark problems tested.“The experimental results show that IFEP performs better than or as well as the better of FEP and CEP for most benchmark problems tested.”