{'fraction_non_alphanumeric': 0.01376720901126408, 'fraction_numerical': 0.0, 'mean_word_length': 4.714285714285714, '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}}
Finding a Path on a Network Subject to Two Constraints Using Genetic Algorithms

Providing end-to-end quality of service (QoS) in packet networks is subject to finding a path that satisfies given constraints. In this paper we study the use of genetic algorithms for finding a path that is subject to two constraints. Variable length chromosomes are used to encode the paths and it is ensured that no cycles included in the paths after crossover operation. Performance of the proposed solution is evaluated by analyzing the effect of population size and mutation rate to the result. Results show that there is a tradeoff between storage and the running time of the solution. Using the proposed approach, in a network with rich connectivity moderate population size generates a result in a short time.