A Distributed Stock Cutting using Mean Field Annealing and Genetic Algorithm
| Autor: | Chul-Eui Hong |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Mathematical optimization
Optimization algorithm Computer Networks and Communications Computer science Distributed computing Message Passing Interface Scrap Data structure Media Technology Rapid convergence Mean field annealing Electrical and Electronic Engineering Stock (geology) Information Systems |
| Zdroj: | Journal of information and communication convergence engineering. 8:13-18 |
| ISSN: | 2234-8255 |
| DOI: | 10.6109/jicce.2010.8.1.013 |
| Popis: | The composite stock cutting problem is defined as allocating rectangular and irregular patterns onto a large composite stock sheet of finite dimensions in such a way that the resulting scrap will be minimized. In this paper, we introduce a novel approach to hybrid optimization algorithm called MGA in MPI (Message Passing Interface) environments. The proposed MGA combines the benefit of rapid convergence property of Mean Field Annealing and the effective genetic operations. This paper also proposes the efficient data structures for pattern related information. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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