{'fraction_non_alphanumeric': 0.020426287744227355, 'fraction_numerical': 0.0026642984014209592, 'mean_word_length': 4.809278350515464, '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 Global Approach to Crew-Pairing Optimization

The problem addressed in this paper is crew-pairing optimization in airline flight planning: finding tours of duty (pairings) that are legal and cover every flight leg at the least cost. The legal rules and cost of a pairing are determined by complex Federal Aviation Agency and contractual requirements. In addition, the problem is made more difficult by the hub-and-spoke system used by airlines that multiplies the possible ways a pairing can link flight legs. The state-of-the-art crew-pairing TRIP system of American Airlines uses subproblem optimization and, as is true for other crew-scheduling systems, may not be able to improve a solution even though a better one exists. We report on the methodology developed during a joint study by IBM and American Airlines Decision Technologies to use the IBM Optimization Subroutine Library in conjunction with TRIP to improve on crew-pairing solutions by taking a global approach. The resulting improvements have been a reduction of 5 to 11 percent in excess crew cost. Estimated total savings are five million dollars per year.