You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/76310
Title: 
Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
Author(s): 
Institution: 
  • Universidade de São Paulo (USP)
  • Universidade Estadual Paulista (UNESP)
Abstract: 
The present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and optimize. This approach is evaluated over sets of benchmark instances and compared to methods from literature. Computational results indicate competitive results applying the proposed method when compared with other literature approaches. © 2013 IEEE.
Issue Date: 
21-Aug-2013
Citation: 
2013 IEEE Congress on Evolutionary Computation, CEC 2013, p. 1483-1490.
Time Duration: 
1483-1490
Keywords: 
  • genetic algorithm
  • hybrid metaheuristic
  • lot-sizing
  • multi-level
  • Capacitated lot sizing problem
  • Computational results
  • Hybrid Meta-heuristic
  • Lot sizing
  • Mixed-Integer Programming
  • Benchmarking
  • Heuristic methods
  • Integer programming
  • Genetic algorithms
Source: 
http://dx.doi.org/10.1109/CEC.2013.6557738
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/76310
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

There are no files associated with this item.
 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.