{'fraction_non_alphanumeric': 0.018912529550827423, 'fraction_numerical': 0.0, 'mean_word_length': 5.465648854961832, '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 New Genetic Algorithm for the Multi-Mode Resource-Constrained Project Scheduling Problem

In this paper we propose a robust genetic algorithm for the multi-mode resourceconstrained project scheduling problem. We present a new representation for the solutions to this problem, which includes an additional bit indicating the scheduling scheme used to construct the schedule, forward or backward. Moreover, we have developed new genetic operators which operate over this representation, exploiting and combining the information in an efficient way. We have designed a new crossover procedure, the two-point forward-backward crossover, and have adapted a mechanism used in a simulated annealing algorithm as a mutation operator in genetic algorithms. Computational results on the standard sets of PSPLIB show the good performance of our algorithm.