The dynamic tugboat scheduling problem is a special kind of Job Scheduling Problem. Here we propose an improved particle swarm optimization (PSO) algorithm in which an entropy function and an elite set is used for better performance. When the entropy of the swarm keeps under some value in a certain period, some of the particles will be replaced randomly by those from the elite set. This may help the swarm to get rid of local optima, and to have a faster convergence. The proposed algorithm is successfully used in the tugboats scheduling problem, and demonstrated its advantages of faster convergence and better result than the standard PSO.
Published in:
Power Electronics and Intelligent Transportation System (PEITS), 2009 2nd International Conference on
(Volume:1
)
Date of Conference: 19-20 Dec. 2009