An adaptive genetic algorithm for solving the single machine scheduling problem with earliness and tardiness penalties

Authors:
Fabio Fernandes Ribeiro;Sergio Ricardo de Souza;Marcone Jamilson Freitas Souza
Affiliations:
DPPG, CEFET/MG, Belo Horizonte, Brazil;DPPG, CEFET/MG, Belo Horizonte, Brazil;Federal University of Ouro Preto, Ouro Preto, Brazil
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

Citing 6
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Abstract

This paper deals with the Single Machine Scheduling Problem with Earliness and Tardiness Penalties, considering distinct time windows and sequence-dependent setup time. Due to the complexity of this problem, an adaptive genetic algorithm is proposed for solving it. Many search operators are used to explore the solution space where the choice probability for each operator depends on the success in a previous search. The initial population is generated by applying GRASP to five dispatch rules. For each individual generated, a polynomial time algorithm is used to determine the initial optimal processing date for each job. During the evaluation process, the best individuals produced by each crossover operator, in each generation undergo refinement in order to improve quality of individuals. Computational results show the effectiveness of the proposed algorithm.