Emergency Surgery Scheduling under Urban Emergencies Based on Improved Moth-flame Optimization

Abstract

This paper analyzes the features of emergency surgeries under urban emergencies, and establishes a model for batch surgery scheduling, taking the issue as the flow-shop scheduling problem (FSP) with parallel machines. The modelling also takes account of the fatigue of doctors after long-term continuous operations, which causes the aging of the operating time and the success rate of saving lives. Then, the improved moth-flame optimization (IMFO) was adopted to solve the established emergency surgery scheduling model. Finally, the proposed model and algorithm were verified through an actual case.

Smart City Emergency Management System design Based on the Internet of Things and Artificial Intelligence Algorithms

“…In recent years, China's Internet of Things industry and technology applications have also developed rapidly, especially to ensure the maintenance of urban life and production [2]. How to reduce and avoid the occurrence of urban emergencies, reduce the losses caused by them, and maintain social stability is a very difficult task for government departments [3].…”