A New Hybrid Elevator Group Control System Scheduling Strategy Based on Artificial Immune Optimization Algorithm
For solving the problem of phenomena of prematurity, random walk in standard genetic algorithm, propose artificial immune optimization algorithm which is derived from simulating the biomechanism. This paper applies artificial immune optimization algorithm on hybrid elevator group control system for optimizing scheduling. Using high cytometaplasia in optimization can avoid local minima and accelerate the optimization. It had made good effect. Comparing with the standard genetic algorithm under the same condition, demonstrates the feasibility and superiority in optimizing scheduling the elevators. The application of artificial immune optimization algorithm on hybrid elevator group control system expands the applied areas of artificial immune algorithm and adds the algorithms for scheduling. This paper prospects for the emphasis of future research and the trend of artificial immune in the end.
Fei Luo Xiaolan Lin Yuge Xu Shihua Wang
College of Automation Science and Engineering South China University of Technology Guangzhou, 510640.
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）