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In this paper we train an Artificial Neural Network (ANN) using Memetic Algorithm (MA) and evaluate its performance on the UCI spambase dataset. The Memetic algorithm incorporates the local search capacity of Simulated Annealing (SA) and the global search capability of Genetic Algorithm (GA) to optimize the parameters of the ANN. The performance of the MA is compared with traditional GA in training...
Graph coloring problem is a classical example for NP-hard combinatorial optimization. Solution to this graph coloring problem often finds its applications to various engineering fields. This paper exhibits the robustness of genetic algorithm to solve a graph coloring. The proposed genetic algorithm employs an innovative single parent conflict gene crossover and a conflict gene mutation as its operators...
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