Hybrid genetic algorithm and simulated annealing approach for the optimization of process plans for prismatic parts
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Publication:4656117
DOI10.1080/00207540110119991zbMath1058.90034OpenAlexW2006324822MaRDI QIDQ4656117
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Publication date: 8 March 2005
Published in: International Journal of Production Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207540110119991
Approximation methods and heuristics in mathematical programming (90C59) Case-oriented studies in operations research (90B90)
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Optimization of process plans using a constraint-based tabu search approach ⋮ A multi-dimensional tabu search algorithm for the optimization of process planning ⋮ Multi-objective dynamic fuzzy scheduling and its algorithm in product collaborative design considering emergency ⋮ A CAPP framework with optimized process parameters for rotational components ⋮ Global optimization of a feature-based process sequence using GA and ANN techniques ⋮ Modelling and optimization of multiple-aspect RMS configurations
Cites Work
- Surface modelling of range data by constrained triangulation
- Operation sequencing in CAPP using genetic algorithms
- Setup planning using Hopfield net and simulated annealing
- Feature-based operation sequence generation in CAPP
- A knowledge-based approach to automated machining process selection and sequencing
- A GA-based approach to machining operation sequencing for prismatic parts
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