{'fraction_non_alphanumeric': 0.024705882352941175, 'fraction_numerical': 0.002352941176470588, 'mean_word_length': 5.257352941176471, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Multi-Objective Genetic Algorithm Based on Objective-Layered to Solve Network Optimization Design

The improved algorithm based on objective layered approach is used to deal with the multi-objective network optimization problem. Based on the traditional non-dominated sorting genetic algorithm, an improved algorithm is given. In order to increase the computational efficiency, the objective layered approach is used sort the individuals of population and identify the non-inferior solution. Individuals are selected by method of loop from the first layer to the m*(1/2) layers(m is total number of layers). Two objectives, the cost and delay are considered. A few examples for the network optimization problems are used test the algorithm. The result shows the algorithm is succeed in finding Pareto solutions with higher computational efficiency.