Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/4287
Título: A genetic algorithm for the job shop scheduling with a new local search using Monte Carlo method
Autor: Magalhães-Mendes, J.
Data: 2011
Editora: ACM
Relatório da Série N.º: AIKED'11;
Resumo: This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.
Peer review: yes
URI: http://hdl.handle.net/10400.22/4287
ISBN: 9789604742738
Versão do Editor: http://dl.acm.org/citation.cfm?id=1959491
Aparece nas colecções:ISEP – CIDEM – Artigos

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
ART_JorgeMagalhaesMendes_2011_CIDEM.pdf95,84 kBAdobe PDFVer/Abrir


FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Degois 

Todos os registos no repositório estão protegidos por leis de copyright, com todos os direitos reservados.