{'fraction_non_alphanumeric': 0.02097902097902098, 'fraction_numerical': 0.002097902097902098, 'mean_word_length': 5.71830985915493, '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}}
Facility Location for Recovering Systems of Interdependent Networks

Modern communities heavily depend on critical infrastructure networks, such as power, water, gas, telecommunications, and transportation. These infrastructure networks are often dependent upon each other for operation. The interdependence of infrastructure networks makes them more vulnerable to disruptive events, such as malevolent attacks, natural disasters, and random failures. Since daily life requires the effective operation of these networks, it is important that they are able to withstand or recover quickly from a disruption. To return the networks to some desired level of performance, work crews must be scheduled to restore certain disrupted components (nodes or links). The proposed model is a multiobjective mixed-integer programming formulation that integrates 1) the order of link and node recovery, 2) the scheduling of recovery tasks to work crews, and 3) the location of facilities (or resources), where each work crew should originate from to effectively facilitate the recovery process. This study demonstrates the use of the model through an illustrative example of two interdependent infrastructure networks that exhibit behaviors of electric power and water networks. Considering four disruption scenarios, the example illustrates how recovery may change by varying the number of facilities established for work crews in each network.