Neural network applied to the coevolution of the memetic algorithm for solving the makespan minimization problem in parallel machine scheduling

Author

Bonfim, Tatiane R. ; Yamakami, Akebo

Author_Institution

Sch. of Electr. & Comput. Eng., State Univ. of Campinas, Brazil

fYear

2002

fDate

2002

Firstpage

197

Abstract

The problem discussed here is one of scheduling the tasks in identical parallel machines. In this problem, we deal with a set of n tasks and m identical parallel machines, with the objective of minimizing the makespan. The makespan is the total processing time of the most busy machine. This work presents an implementation of a memetic-neuro scheduler for solving this scheduling problem. The memetic algorithm, which is an hybrid version of genetic algorithm with local search, has been used to evolve good scheduling forms; and the neural network has been used to calculate the fitness for each individual of the population.

Keywords

backpropagation; computer aided production planning; genetic algorithms; minimisation; neural nets; production control; resource allocation; backpropagation; coevolution; genetic algorithm; makespan minimization; memetic algorithm; neural network; parallel machine scheduling; production control; reinforcement learning; resource allocation; Computer networks; Genetic algorithms; Intelligent networks; Learning; Minimization methods; Neural networks; Neurons; Parallel machines; Processor scheduling; Scheduling algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2002. SBRN 2002. Proceedings. VII Brazilian Symposium on

Print_ISBN

0-7695-1709-9

Type

conf

DOI

10.1109/SBRN.2002.1181473

Filename

1181473