J-060

The Acceleration of Evolutionary Computations Using Fitness Estimation

Authors: Yasushi Hanaki(*), Tomonori Hashiyama(**), Shigeru Okuma(*)
Affiliation: Nagoya University(*)
Nagoya Industrial Science Research Institute(**)

Abstract
Evolutionary Computation(EC) is widely applied to various kinds of combinatorial optimization problems. ECs are generally time-consuming paradigm because they need much trial and error. To accelerate ECs, some modification methods of genetic operator have been proposed such as improving mutation and recombination of chromosomes and/or their control parameters and so on. Through these modification, ECs can find the suboptimal solutions in the relatively early generations.

In spite of these improvements, ECs still require much time to obtain the solution. In many engineering applications of ECs, fitness evaluation spent the most of the computational time. This paper presents a new approach on the acceleration of ECs by reducing the time for fitness evaluation. Saving the time for fitness evaluation results in accelerating the ECs in time domain. In the proposed method, only one individual of the population is actually evaluated in each generation. Fitness values for the rest of the population are estimated with simple calculation. Although the errors of estimation may decelerate the ECs in generation domain, the saving time in evaluation scheme will exceeds the deceleration. As a result, we can obtain suboptimal solution relatively faster.

The simulation results of the designing fuzzy logic controller using GA shows the effectiveness of the proposed method to accelerate the evolution in time domain using estimated evaluation.

Yasushi Hanaki
hanaki@okuma.nuee.nagoya-u.ac.jp