{'fraction_non_alphanumeric': 0.02, 'fraction_numerical': 0.0, 'mean_word_length': 5.326315789473684, '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 population based-approach to address real-life transport on-demand problems

This work aims at improving the quality of the service provided to the customers within real-life demand-responsive transportation systems. To this end, a new customer-oriented problem is designed to minimize both total transit time for the transportation service providers and total waiting time for the travellers. To solve the new problem, an evolutionary algorithm is proposed and compared with a hybrid evolutionary one from the literature. Preliminary computational experiments show the effectiveness of our method.