Genetic algorithm for job-shop scheduling with operators

Authors:
Raúl Mencía;María R. Sierra;Carlos Mencía;Ramiro Varela
Affiliations:
Department of Computer Science, University of Oviedo, Gijón, Spain;Department of Computer Science, University of Oviedo, Gijón, Spain;Department of Computer Science, University of Oviedo, Gijón, Spain;Department of Computer Science, University of Oviedo, Gijón, Spain
Venue:
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
Year:
2011

Citing 3
Cited 0

A branch and bound algorithm for the job-shop scheduling problem

Discrete Applied Mathematics - Special volume: viewpoints on optimization
A job-shop problem with one additional resource type

Journal of Scheduling
New codification schemas for scheduling with genetic algorithms

IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

We face the job-shop scheduling problem with operators. To solve this problem we propose a new approach that combines a genetic algorithm with a new schedule generation scheme.We report results from an experimental study across conventional benchmark instances showing that our approach outperforms some current state-of-the-art methods.