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

Volume

1

fYear

2005

Firstpage

150

Lastpage

154

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Brain, 2005. ICNN&B '05. International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9422-4

Type

conf

DOI

10.1109/ICNNB.2005.1614587

Filename

1614587