EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION VIA DIFFERENTIAL EVOLUTION

Ph.DDOCTOR OF PHILOSOPH

Using adaptive operators in genetic search

Abstract. In this paper, we provided an extension of our previous work on adaptive genetic algorithm [1]. Each individual encodes the probability (rate) of its genetic operators. In every generation, each individual is modified by only one operator. This operator is selected according to its encoded rates. The rates are updated according to the performance achieved by the offspring (compared to its parents) and a random learning rate. The proposed approach is augmented with a simple transposition operator and tested on a number of benchmark functions. 1 Simplified Hybrid Adaptive Evolutionary Algorithm (SHA-EA) Parameter Adaptation (PA) eliminates the parameter setting of evolutionary algorithms (EAs) by adapting those through the execution of the EA [2,3]. Several PA techniques have been developed [2,4,5]. We introduced an hybrid technique for adapting genetic operator probabilities in our previous work [1]. The operator probabilities along with a learning rule rate, which determines the reward/punishment factor on the operator rate, were encoded in each individual. In this paper, we removed the encoding of the learning rate and simulated it with a uniform random rate [0,1]. Also, we used standard operators that only modify the solution part. When a non-unary operator is selected, the additional parents are chosen with a local selection strategy. The operator rates are evolved according to the performance achieved by the offspring (compared to its parent) and the random learning rate generated, according to the Algorithm 1. We tested several functions using different sets of operators. We used elitist selection as replacement strategy, with each EA run for 1000 iterations, and reported the results averaging 50 run. We used a population of 100 individual for binary functions and 200 for real valued functions, using 32 bits for encoding each real value. Table 1, compares the results obtained by SHA-EA with some reported results in the literature.