Knowledge insertion: An efficient approach to reduce effort in simple algorithms for unrestricted parallel equal machines scheduling

GECCO 2005 - Genetic and Evolutionary Computation Conference

Volumn , Issue , 2005, Pages 1587-1588

  Ferretti, Edgardo ^a   Esquivel, Susana ^a  

^a UNIVERSIDAD NACIONAL DE SAN LUIS   (Argentina)

Author keywords

Artificial Intelligence; Genetic Algorithms; Scheduling

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATION THEORY; COSTS; HEURISTIC METHODS; PROBLEM SOLVING; SCHEDULING;

CONVENTIONAL HEURISTICS; KNOWLEDGE INSERTION; PARALLEL MACHINES SCHEDULING SYSTEMS; SIMPLE GENETIC ALGORITHMS (SGA);

GENETIC ALGORITHMS;

EID: 32444450173     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1068009.1068272     Document Type: Conference Paper

References (4)

1. J. Beasley. Or library. http://people.brunel.ac.uk/~mastjjb/jeb/info.html. Scheduling: Weighted Tardiness.
2. H. A. J. Crauwels, C. N. Potts, and L. N. VanWassenhove. Local search heuristics for the single machine total weighted tardiness scheduling problem. INFORMS J. on Computing, 10(3):341-350, 1998.
3. T. Morton and D. Pentico. Heuristic Scheduling Systems. John Wiley and Sons, New York, 1993.
4. M. Pinedo. Scheduling: Theory, Algorithms and System. Prentice Hall, 1995.