A Robust Solution Searching Scheme in Genetic Search
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Trade-off between performance and robustness: an evolutionary multiobjective approach
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Genetic algorithms with a robust solution searching scheme
IEEE Transactions on Evolutionary Computation
Robust design of multilayer optical coatings by means ofevolutionary algorithms
IEEE Transactions on Evolutionary Computation
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Evolutionary optimization in uncertain environments-a survey
IEEE Transactions on Evolutionary Computation
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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.