Abstract
For overcoming the disadvantage of local optimum and slower convergence speed of general genetic algorithms, an improved genetic algorithm with dynamic regulation parameters was proposed in this paper by introducing the variance and expectation of individual adaptive value to describe concentration-dissipation degree of population. The validity of this improved genetic algorithm is verified by simulation examples. The improved algorithm is also been applied to optimal combination stacking of steel roll in a batch annealing shop and a satisfactory result is obtained in production.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Published version (
Free)
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
