Fitness function for finding out robust solutions on time-varying functions

ABSTRACT

Evolutionary Computations in dynamic/uncertain environments have attracted much attention. Studies regarding this research subjects can be classified into four categories: Noise, Robustness, Fitness approximation, and Time-Varying function. In research on Time-Varying function, the tracking property over changes of fitness landscape has been broadly and deeply researched so far. In this paper, instead of tracking new peaks, robust solution to Time-Varying functions is introduced. Moreover, two weighted fitness functions, Exponential Weight and Linear Weight, are proposed. Experiments on modified Branke's benchmark problems on Time-Varying function reveal the effectiveness of the weighted approaches.

REFERENCES

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INDEX TERMS

Primary Classification:
  F. Theory of Computation
  F.1 COMPUTATION BY ABSTRACT DEVICES
      F.1.2 Modes of Computation
          Subjects: Probabilistic computation

Additional Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search

General Terms:
Algorithms

Keywords:
dynamic environments, robust solution, time-varying functions