Title :
Precast production scheduling with genetic algorithms
Author :
Chan, W.T. ; Hu, H.
Author_Institution :
Nat. Univ. of Singapore, Singapore
Abstract :
A flow shop sequencing model (FSSM) that incorporates actual constraints encountered in practice is proposed for the difficult case of specialized precast production scheduling. The model is solved using a genetic algorithm (GA). The traditional minimize makespan and the more practical minimize tardiness penalty objective functions are optimized separately, as well as simultaneously using a weighted approach. Experiments are conducted to investigate the effect of increasing population size and seeding the initial population with heuristic solutions. Comparisons between the GA and classical heuristic rules show that the GA is competitive, if not better than heuristic rules in discovering a set of good solutions
Keywords :
genetic algorithms; heuristic programming; production control; constraints; flow shop sequencing model; genetic algorithms; heuristic rules; heuristic solution seeding; minimize makespan penalty objective function; minimize tardiness penalty objective function; population size; precast production scheduling; weighted approach; Artificial intelligence; Genetic algorithms; Humans; Job shop scheduling; Mathematical programming; Operations research; Processor scheduling; Production planning; Resource management; Single machine scheduling;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870768