Title :
Genetic annealing algorithm for cutting stock problem in furniture industry
Author :
Yue, Qi ; Gao, Lewen
Author_Institution :
Northeast Forestry Univ., Harbin, China
Abstract :
Cutting stock problem is to save material and optimize the utilizing of the resources, which is being widely used in product designing, manufacturing and applying. It is very complicated and difficult in terms of the calculation theory. This paper analyzed the Genetic Annealing Algorithm and applied it in the area of stock cutting optimization of fiberboard furniture. This paper presented the key procedures and methods based on the mathematical comments, and took an example of temperature control of simulated annealing algorithm that is enhanced the standard Genetic Annealing Algorithm. The instance of this algorithm shows that it can solve the stock cutting optimization of rectangular material more quickly and efficiently.
Keywords :
bin packing; furniture industry; genetic algorithms; product design; simulated annealing; cutting stock problem; fiberboard furniture; furniture industry; genetic annealing algorithm; product design; simulated annealing; stock cutting optimization; Algorithm design and analysis; Design optimization; Forestry; Genetics; Manufacturing industries; Mathematical model; Polynomials; Production; Raw materials; Simulated annealing; Furniture Cutting Stock; Genetic Algorithm; Genetic Annealing Algorithm; Rectangular Layout Problem; Simulated Annealing Algorithm;
Conference_Titel :
Computer-Aided Industrial Design & Conceptual Design, 2009. CAID & CD 2009. IEEE 10th International Conference on
Conference_Location :
Wenzhou
Print_ISBN :
978-1-4244-5266-8
Electronic_ISBN :
978-1-4244-5268-2
DOI :
10.1109/CAIDCD.2009.5374979