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Comparison of Four Population-Based Meta-Heuristic Algorithms on Pick-and-Place Optimization
- Source :
- Procedia Manufacturing. 17:944-951
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- This paper applies four population-based classical meta-heuristic algorithms to solve a pick-and-place optimization problem for a surface mounter in a PCB assembly environment. A mathematical model of this optimization problem is formulated as an integrated problem of the capacitated vehicle routing problem and the quadratic assignment problem, which are well-known NP-hard problems. A brief description of each method is presented and special operators for the integer encoded solutions are developed. Ten real-world PCB samples are tested and optimized using all the four algorithms. The experiment results show that the genetic algorithm has better performance than the others in terms of solution quality, especially the deviation of results from multiple trials, and computation time.
- Subjects :
- 0209 industrial biotechnology
education.field_of_study
Optimization problem
Quadratic assignment problem
Computer science
Computation
Population
02 engineering and technology
Industrial and Manufacturing Engineering
020901 industrial engineering & automation
Artificial Intelligence
Vehicle routing problem
Genetic algorithm
0202 electrical engineering, electronic engineering, information engineering
SMT placement equipment
020201 artificial intelligence & image processing
education
Algorithm
Integer (computer science)
Subjects
Details
- ISSN :
- 23519789
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- Procedia Manufacturing
- Accession number :
- edsair.doi...........bfa596c1365a9158510554bfd69a35ae