{'fraction_non_alphanumeric': 0.01893939393939394, 'fraction_numerical': 0.0, 'mean_word_length': 5.3293413173652695, '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}}
Optimal multiunit transfer over adversarial paths with increasing intercept probabilities

Abstract We consider a problem involving transporting a set of items over a set of hostile paths where an adversary seeks to intercept them, with the goal of maximizing the probability that all items successfully cross. Items leave a unique footprint as they cross a path, and the probability that an item is intercepted on a given path increases according to an intercept probability function as the cumulative footprint on that path increases. We provide a problem formulation and demonstrate several properties important for its solution. We then use these to develop four optimization algorithms: an exact algorithm (E), a greedy heuristic (G), a greedy heuristic with local search (LS), and a genetic algorithm (GA). These algorithms were evaluated via computational experiments on a large set of benchmark problems spanning different sizes and characteristics. LS provided the largest number of best solutions while outperforming GA in terms of solution time.