The tenth annual IEEE International Conference on Automation Science and Engineering (IEEE CASE 2014) was held recently in New Taipei City, Taiwan. At the conference, Jie Song, Assistant Professor in the Department of Industrial Engineering and Management, College of Engineering, won the Best Conference paper Award.

The conference was jointly organized by IEEE Robotics and Automation Society (IEEE RAS), National Taiwan University, and National Cheng Kung University, with the theme "Frontiers of Intelligent Automation Science and Technology for Better Quality of Life". Academics and industry experts in the field of automation from around the world attended the conference.

IEEE CASE, now in its tenth year, is the authoritative academic conference in the field of automation. It invited elite scholars in the field of automation from worldwide to participate and share research results and experiences, and to have face to face communications with others in order to promote the advancement of automation technology. In addition to publishing conference papers, it also invited many academic heavyweights to deliver keynote addresses, providing valuable experience for the participants and helping expand their research horizons.

Song presented on the conference her research team’s latest progress in optimizing patient flow among multi-level medical systems. Their paper submitted was entitled “A Simulation Based GA for Multi-objective Optimization in Patient Flow Distribution”.

Their study proposed a multi-objective optimization method based on a combination of discrete event simulation and genetic algorithms, and conducted site visits and modeling optimization to China's urban multi-level health systems. The paper discussed optimized patient flow distribution among regions including Grade Three comprehensive  hospitals and community health centers, addressing the problem of uneven allocation of medical resources, and providing quantitative patients allocation strategy to ease the current difficulties in seeing a doctor. The method can automatically get "Pareto" optimal solutions in patients flow distribution based on actual management experience.

The paper passed a rigorous appraisal of the conference academic committee made up of multinational experts and won the Best Conference Paper Award.

The study was funded by the National Natural Science Foundation and other projects. Other collaborators include Yunzhe Qiu, a master student of the College of Engineering and Zekun Liu, a student of the School of Mathematical Sciences, all from Peking University.