Evolutionary Optimization of Airport Security Inspection Allocation

摘要

Airport security inspection plays a vital role in protecting flights and passengers. However, assigning a large number of baggages to different inspection devices and personnel can be a difficult problem. In this paper, we present a security inspection assignment problem (SIAP) for maximizing the overall probability of detecting hazardous goods within a limited time period. We then propose a hybrid evolutionary algorithm, named DE-DNSPSO, which combines differential evolution (DE) with the diversity enhanced particle swarm optimization with neighborhood search (DNSPSO) to efficiently solve the problem. In DE-DNSPSO, DE operators are used to further improve the diversity enhancing mechanism of DNSPSO and thus better balance exploration and exploitation of the algorithm. Experimental results show that DE-DNSPSO performs better than DNSPSO and some other well-known algorithms on a set of test instances, and our approach contributes to the improvement of inspection capability of airports.