{'fraction_non_alphanumeric': 0.02666666666666667, 'fraction_numerical': 0.0016666666666666668, 'mean_word_length': 5.260416666666667, '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}}
Multi-objective differential evolution algorithm based on the non-uniform mutation

A multi-objective differential evolution algorithm based on the non-uniform MDEM is proposed. MDEM employs the (μ + λ) selection strategy and non-uniform mutation operator to generate new population. The non-uniform mutation operator not only increased the pressure of the choice of MDEM algorithm, but also maintained the population diversity. We compare MDEM with NSGA-II, SPEA2 and DEMO by the numerical experiments on eight benchmark problems to find that MDEM has better computational results and effectiveness.