智能科学与技术学报 (Jun 2020)
An intelligent optimization scheduling method for community patrolling and investigation in epidemic situations
Abstract
Community plays an important role in epidemic prevention and control in the society.Based on the practical experience of community prevention and control of the novel corona virus pneumonia,a community patrolling and investigation scheduling problem in epidemic situations was presented,which estimated a risk value for each high-risk household based on epidemic-related information,and then scheduled the community staffs to patrol and investigate the high-risk households as efficiently as possible.To solve this problem,a hybrid intelligent optimization scheduling algorithm was proposed,which explored the solution space based on the search strategy of the water wave optimization (WWO) met heuristic and improved solution accuracies using two local search strategies.Whenever an exceptional case was detected during the patrolling and investigation,the solution was dynamically adapted to the changed situation.Computational results on the real-world cases of community patrolling and investigation in Zhejiang Province,China demonstrate the effectiveness and efficiency of the proposed method.
