Title :
Hybrid Genetic Algorithm for Minimizing the Range of Lateness and Make-span on Non-identical Parallel Machines
Author :
Huang, Decai ; Guo, Haidong ; Qian, Neng
Author_Institution :
Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou
Abstract :
A hybrid genetic algorithm is presented for minimizing the range of lateness and make-span on parallel non-identical machines in this paper, and a dynamic fitness function is introduced too. The coding method of the hybrid genetic algorithm (HGA) is very simple because it utilized the property of effective optimal algorithm for solving the corresponding single machine problem. It made the implement of HGA be very easy. Numerical simulations illustrate that the HGA has the property of fast convergence, and can be used to solve larger size problems
Keywords :
genetic algorithms; single machine scheduling; dynamic fitness function; hybrid genetic algorithm; job scheduling; nonidentical parallel machines; single machine scheduling; Convergence of numerical methods; Educational institutions; Genetic algorithms; Job shop scheduling; Machining; Mathematical model; Numerical simulation; Parallel machines; Production management; Single machine scheduling; genetic algorithm; job scheduling; parallel machines;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614587
