The Improvement of Multidisciplinary Clinical Process by Using Ant Colony Adaptive Fuzzy Degree System

Recent changes in health care have focused attention on new tools for planning and managing clinical processes.The knowledge for the improvement of redesigning clinical process is important for medical quality.This paper proposes a modified ant colony system(ACS)using adaptive fuzzy degree approach(MACS)for modeling and designing a new multidisciplinary clinical process.In the ACS algorithm,the ants find an optimal solution according to the pheromone strength.But,ACS has a problem which is to fall into local solution.In this paper,a modified lower limit of the fuzzy degree is proposed,that each node has its own lower limit in the traveling salesman problem(TSP).This is also called node margin value.The proposed method is applied to the ACS and local search 2-opt algorithm.It can speed up the convergent process and improve the efficiency and the error rate for simulation results.The experiments are demonstrated and verified by the international benchmarks with TSPLIB and compared with the GA of LaLena,AFD-GA and ACS.
ant colony system adaptive fuzzy degree traveling salesman problem 2-opt multidisciplinary clinical processes
Telung Pan Jhih-Chung Chang
Department of Planning and Management St.Josephs Hospital Yunlin,Taiwan 63241 Department of Information Technology Ling Tung University Taichung,Taiwan 40852
国际会议
The 2014 ICME International Conference on Complex Medical Engineering (CME2014)ICME复合医学工程国际会议
台北
英文
227-232
2014-06-26(万方平台首次上网日期,不代表论文的发表时间)