An introduction to genetic algorithms
An introduction to genetic algorithms
Classical floorplanning harmful?
ISPD '00 Proceedings of the 2000 international symposium on Physical design
A comparative analysis of search methods as applied to shearographic fringe modelling
IEA/AIE '00 Proceedings of the 13th international conference on Industrial and engineering applications of artificial intelligence and expert systems: Intelligent problem solving: methodologies and approaches
The irregular cutting-stock problem mdash; a new procedure for deriving the no-fit polygon
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Genetic Algorithm Coding Methods for Leather Nesting
Applied Intelligence
| Hi-index | 0.00 |
The problem of placing a number of specific shapes in order to minimise material waste is commonly encountered in the sheet metal, clothing and shoe-making industries. It is driven by the demand to find a layout of non-overlapping parts in a set area in order to maximise material utilisation. A corresponding problem is one of compaction, which is to minimise the area that a set number of shapes can be placed without overlapping. This paper presents a novel connectivity based approach to leather part compaction using the no-fit polygon (NFP). The NFP is computed using an image processing method as the boundary of the Minkowski sum, which is the convolution between two shapes at given orientations. These orientations along with shape order and placement selection constitute the chromosome structure.