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A binary particle swarm optimization approach to optimize assembly sequence planning

This paper presents an approach of applying Binary Particle Swarm Optimization (BPSO) algorithm to an assembly sequence-planning (ASP) problem. Permutation encoding of sequences is used to represent particles, then those particles are strictly subjected to a precedence constraint matrix at which onl...

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Main Authors: Ahmed Mukred, Jameel Abdulla, Ibrahim, Zuwairie, Ismail, Ibrahim, Mokhtar, Norrima
Format: Conference or Workshop Item
Published: 2011
Online Access:http://eprints.utm.my/id/eprint/45464/
https://www.researchgate.net/publication/240917767_A_Binary_Particle_Swarm_Optimization_Approach_to_Optimize_Assembly_Sequence_Planning
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spelling my.utm.454642017-09-20T00:34:47Z http://eprints.utm.my/id/eprint/45464/ A binary particle swarm optimization approach to optimize assembly sequence planning Ahmed Mukred, Jameel Abdulla Ibrahim, Zuwairie Ismail, Ibrahim Mokhtar, Norrima This paper presents an approach of applying Binary Particle Swarm Optimization (BPSO) algorithm to an assembly sequence-planning (ASP) problem. Permutation encoding of sequences is used to represent particles, then those particles are strictly subjected to a precedence constraint matrix at which only the feasible sequences will be iterated in the process. An archive is used in storing the feasible sequences and a swap mechanism is used to identify the feasible sequences for iteration. As the nature of assembly sequence planning is a discrete type of problem Binary PSO technique is used. 2011 Conference or Workshop Item PeerReviewed Ahmed Mukred, Jameel Abdulla and Ibrahim, Zuwairie and Ismail, Ibrahim and Mokhtar, Norrima (2011) A binary particle swarm optimization approach to optimize assembly sequence planning. In: 2nd International Symposium On Mechanical Science And Technology (ISMST 2011). https://www.researchgate.net/publication/240917767_A_Binary_Particle_Swarm_Optimization_Approach_to_Optimize_Assembly_Sequence_Planning
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
description This paper presents an approach of applying Binary Particle Swarm Optimization (BPSO) algorithm to an assembly sequence-planning (ASP) problem. Permutation encoding of sequences is used to represent particles, then those particles are strictly subjected to a precedence constraint matrix at which only the feasible sequences will be iterated in the process. An archive is used in storing the feasible sequences and a swap mechanism is used to identify the feasible sequences for iteration. As the nature of assembly sequence planning is a discrete type of problem Binary PSO technique is used.
format Conference or Workshop Item
author Ahmed Mukred, Jameel Abdulla
Ibrahim, Zuwairie
Ismail, Ibrahim
Mokhtar, Norrima
spellingShingle Ahmed Mukred, Jameel Abdulla
Ibrahim, Zuwairie
Ismail, Ibrahim
Mokhtar, Norrima
A binary particle swarm optimization approach to optimize assembly sequence planning
author_facet Ahmed Mukred, Jameel Abdulla
Ibrahim, Zuwairie
Ismail, Ibrahim
Mokhtar, Norrima
author_sort Ahmed Mukred, Jameel Abdulla
title A binary particle swarm optimization approach to optimize assembly sequence planning
title_short A binary particle swarm optimization approach to optimize assembly sequence planning
title_full A binary particle swarm optimization approach to optimize assembly sequence planning
title_fullStr A binary particle swarm optimization approach to optimize assembly sequence planning
title_full_unstemmed A binary particle swarm optimization approach to optimize assembly sequence planning
title_sort binary particle swarm optimization approach to optimize assembly sequence planning
publishDate 2011
url http://eprints.utm.my/id/eprint/45464/
https://www.researchgate.net/publication/240917767_A_Binary_Particle_Swarm_Optimization_Approach_to_Optimize_Assembly_Sequence_Planning
_version_ 1643651747631071232
score 13.211869

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