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AuthorMusharavati, Farayi
AuthorHamouda, Abdelmagid Salem
Available date2016-01-18T13:34:43Z
Publication Date2015-03
Publication NameThe International Journal of Advanced Manufacturing Technology
Citation"Multiple parts process planning in serial–parallel flexible flow lines: part II—solution method based on genetic algorithms with fixed- and variable-length chromosomes", Musharavati, Farayi and Hamouda, Abdelmagid Salem , The International Journal of Advanced Manufacturing Technology, 2015, 77(5): 1105-1143
ISSN0268-3768
ISSN1433-3015 (online)
URIhttp://dx.doi.org/10.1007/s00170-014-6459-2
URIhttp://hdl.handle.net/10576/4104
AbstractMultiple parts process planning (MPPP) is a hard optimization problem that requires the rigor and intensity of metaheuristic-based algorithms such as simulated annealing and genetic algorithms. In this paper, a solution method for this problem is developed based on genetic algorithms. Genetic algorithms solve problems by exploring a given search space. To do this, a landscape over which the search traverses is constructed based on a number of algorithm choices. Key algorithm choices include (a) type of chromosome representation, which affects the efficiency of an algorithm, and (b) type and form of genetic operators, which affect the effectiveness of an algorithm. More specifically, the suitability of a variable-length chromosome (VLC) representation for encoding a solution to a MPPP problem is investigated. The effectiveness and efficiency of implementing the VLC algorithm is analyzed and compared with: (a) the commonly used fixed-length chromosome representation, (b) a variant of the simulated annealing algorithm, and (c) a knowledge-informed simulated annealing algorithm. The scalability of the algorithms is analyzed and their effectiveness demonstrated by experimental results based on four problem sizes. Obtained results show that, although there are variances in performances, all algorithms investigated are capable of obtaining good solutions. In addition, variances were observed for different aspects of the MPPP problem. The results indicate that the VLC algorithm is effective in solving MPPP problems that consider multiple aspects in the search for optimal process planning solutions.
Languageen
PublisherSpringer London
Relationhttp://hdl.handle.net/10576/4103
SubjectMultiple parts process planning (MPPP)
Serial–parallel flow lines
Flexibility
Genetic algorithms (GAs)
Variable length chromosomes (VLC)
Fixed-length chromosomes (FLC)
Simulated annealing (SA)
TitleMultiple parts process planning in serial–parallel flexible flow lines: part II—solution method based on genetic algorithms with fixed- and variable-length chromosomes
TypeArticle
Pagination1105-1143
Issue Number5
Volume Number77


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