- Title
- A general genetic algorithm for one and two dimensional cutting and packing problems
- Creator
- Mancapa, Vusisizwe
- Subject
- Packaging -- Data processing
- Subject
- Genetic algorithms
- Subject
- Cutting stock problem
- Subject
- Packing for shipment
- Subject
- Manufacturing processes -- Planning
- Date Issued
- 2007
- Date
- 2007
- Type
- Thesis
- Type
- Masters
- Type
- MTech
- Identifier
- vital:9602
- Identifier
- http://hdl.handle.net/10948/555
- Identifier
- http://hdl.handle.net/10948/d1011727
- Identifier
- Packaging -- Data processing
- Identifier
- Genetic algorithms
- Identifier
- Cutting stock problem
- Identifier
- Packing for shipment
- Identifier
- Manufacturing processes -- Planning
- Description
- Cutting and packing problems are combinatorial optimisation problems. The major interest in these problems is their practical significance, in manufacturing and other business sectors. In most manufacturing situations a raw material usually in some standard size has to be divided or be cut into smaller items to complete the production of some product. Since the cost of this raw material usually forms a significant portion of the input costs, it is therefore desirable that this resource be used efficiently. A hybrid general genetic algorithm is presented in this work to solve one and two dimensional problems of this nature. The novelties with this algorithm are: A novel placement heuristic hybridised with a Genetic Algorithm is introduced and a general solution encoding scheme which is used to encode one dimensional and two dimensional problems is also introduced.
- Format
- xiii, 189 leaves
- Format
- Publisher
- Nelson Mandela Metropolitan University
- Publisher
- Faculty of Engineering, the Built Environment and Information Technology
- Language
- English
- Rights
- Nelson Mandela Metropolitan University
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