Assembly sequence planning using hybrid binary particle swarm optimization
Assembly Sequence Planning (ASP) is known as a large-scale, timeconsuming combinatorial problem. Therefore time is the main factor in production planning. Recently, ASP in production planning had been studied widely especially to minimize the time and consequently reduce the cost. The first objectiv...
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my-utm-ep.780882018-07-23T06:10:23Z Assembly sequence planning using hybrid binary particle swarm optimization 2014-12 Ahmed Mukred, Jameel Abdulla TK Electrical engineering. Electronics Nuclear engineering Assembly Sequence Planning (ASP) is known as a large-scale, timeconsuming combinatorial problem. Therefore time is the main factor in production planning. Recently, ASP in production planning had been studied widely especially to minimize the time and consequently reduce the cost. The first objective of this research is to formulate and analyse a mathematical model of the ASP problem. The second objective is to minimize the time of the ASP problem and hence reduce the product cost. A case study of a product consists of 19 components have been used in this research, and the fitness function of the problem had been calculated using Binary Particle Swarm Optimization (BPSO), and hybrid algorithm of BPSO and Differential Evolution (DE). The novel algorithm of BPSODE has been assessed with performance-evaluated criteria (performance measure). The algorithm has been validated using 8 comprehensive benchmark problems from the literature. The results show that the BPSO algorithm has an improved performance and can reduce further the time of assembly of the 19 parts of the ASP compared to the Simulated Annealing and Genetic Algorithm. The novel hybrid BPSODE algorithm shows a superior performance when assessed via performance-evaluated criteria compared to BPSO. The BPSODE algorithm also demonstrated a good generation of the recorded optimal value for the 8 standard benchmark problems. 2014-12 Thesis http://eprints.utm.my/id/eprint/78088/ http://eprints.utm.my/id/eprint/78088/1/JameelAbdullaAhmedPFKE2014.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:98313 phd doctoral Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering |
| institution |
Universiti Teknologi Malaysia |
| collection |
UTM Institutional Repository |
| language |
English |
| topic |
TK Electrical engineering Electronics Nuclear engineering |
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TK Electrical engineering Electronics Nuclear engineering Ahmed Mukred, Jameel Abdulla Assembly sequence planning using hybrid binary particle swarm optimization |
| description |
Assembly Sequence Planning (ASP) is known as a large-scale, timeconsuming combinatorial problem. Therefore time is the main factor in production planning. Recently, ASP in production planning had been studied widely especially to minimize the time and consequently reduce the cost. The first objective of this research is to formulate and analyse a mathematical model of the ASP problem. The second objective is to minimize the time of the ASP problem and hence reduce the product cost. A case study of a product consists of 19 components have been used in this research, and the fitness function of the problem had been calculated using Binary Particle Swarm Optimization (BPSO), and hybrid algorithm of BPSO and Differential Evolution (DE). The novel algorithm of BPSODE has been assessed with performance-evaluated criteria (performance measure). The algorithm has been validated using 8 comprehensive benchmark problems from the literature. The results show that the BPSO algorithm has an improved performance and can reduce further the time of assembly of the 19 parts of the ASP compared to the Simulated Annealing and Genetic Algorithm. The novel hybrid BPSODE algorithm shows a superior performance when assessed via performance-evaluated criteria compared to BPSO. The BPSODE algorithm also demonstrated a good generation of the recorded optimal value for the 8 standard benchmark problems. |
| format |
Thesis |
| qualification_name |
Doctor of Philosophy (PhD.) |
| qualification_level |
Doctorate |
| author |
Ahmed Mukred, Jameel Abdulla |
| author_facet |
Ahmed Mukred, Jameel Abdulla |
| author_sort |
Ahmed Mukred, Jameel Abdulla |
| title |
Assembly sequence planning using hybrid binary particle swarm optimization |
| title_short |
Assembly sequence planning using hybrid binary particle swarm optimization |
| title_full |
Assembly sequence planning using hybrid binary particle swarm optimization |
| title_fullStr |
Assembly sequence planning using hybrid binary particle swarm optimization |
| title_full_unstemmed |
Assembly sequence planning using hybrid binary particle swarm optimization |
| title_sort |
assembly sequence planning using hybrid binary particle swarm optimization |
| granting_institution |
Universiti Teknologi Malaysia, Faculty of Electrical Engineering |
| granting_department |
Faculty of Electrical Engineering |
| publishDate |
2014 |
| url |
http://eprints.utm.my/id/eprint/78088/1/JameelAbdullaAhmedPFKE2014.pdf |
| _version_ |
1747817904053682176 |