GOMEZ, Alberto ;DE LA FUENTE, David ;PUENTE, Javier ;PARREÑO, José . The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 51, n.5, p. 234-239, august 2017. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/sl/article/the-resolution-of-packing-problems-using-simulated-annealing-and-genetic-algorithms/>. Date accessed: 20 dec. 2024. doi:http://dx.doi.org/.
Gomez, A., de la Fuente, D., Puente, J., & Parreño, J. (2005). The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms. Strojniški vestnik - Journal of Mechanical Engineering, 51(5), 234-239. doi:http://dx.doi.org/
@article{., author = {Alberto Gomez and David de la Fuente and Javier Puente and José Parreño}, title = {The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {51}, number = {5}, year = {2005}, keywords = {genetic algorithms; packing; cutting processes; process optimization; }, abstract = {The aim of this paper is to present two algorithms that are designed to optimise the cutting process of an L-type guillotine and to minimise the number of sheets used to manufacture a number of rectangular pieces. Two algorithms are proposed, one based on genetic algorithms and the other on simulated annealing. They are compared with the help of a bank of examples. Both algorithms provide very good results, although each of them has its peculiarities, which are described in this paper.}, issn = {0039-2480}, pages = {234-239}, doi = {}, url = {https://www.sv-jme.eu/sl/article/the-resolution-of-packing-problems-using-simulated-annealing-and-genetic-algorithms/} }
Gomez, A.,de la Fuente, D.,Puente, J.,Parreño, J. 2005 August 51. The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 51:5
%A Gomez, Alberto %A de la Fuente, David %A Puente, Javier %A Parreño, José %D 2005 %T The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms %B 2005 %9 genetic algorithms; packing; cutting processes; process optimization; %! The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms %K genetic algorithms; packing; cutting processes; process optimization; %X The aim of this paper is to present two algorithms that are designed to optimise the cutting process of an L-type guillotine and to minimise the number of sheets used to manufacture a number of rectangular pieces. Two algorithms are proposed, one based on genetic algorithms and the other on simulated annealing. They are compared with the help of a bank of examples. Both algorithms provide very good results, although each of them has its peculiarities, which are described in this paper. %U https://www.sv-jme.eu/sl/article/the-resolution-of-packing-problems-using-simulated-annealing-and-genetic-algorithms/ %0 Journal Article %R %& 234 %P 6 %J Strojniški vestnik - Journal of Mechanical Engineering %V 51 %N 5 %@ 0039-2480 %8 2017-08-18 %7 2017-08-18
Gomez, Alberto, David de la Fuente, Javier Puente, & José Parreño. "The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms." Strojniški vestnik - Journal of Mechanical Engineering [Online], 51.5 (2005): 234-239. Web. 20 Dec. 2024
TY - JOUR AU - Gomez, Alberto AU - de la Fuente, David AU - Puente, Javier AU - Parreño, José PY - 2005 TI - The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms JF - Strojniški vestnik - Journal of Mechanical Engineering DO - KW - genetic algorithms; packing; cutting processes; process optimization; N2 - The aim of this paper is to present two algorithms that are designed to optimise the cutting process of an L-type guillotine and to minimise the number of sheets used to manufacture a number of rectangular pieces. Two algorithms are proposed, one based on genetic algorithms and the other on simulated annealing. They are compared with the help of a bank of examples. Both algorithms provide very good results, although each of them has its peculiarities, which are described in this paper. UR - https://www.sv-jme.eu/sl/article/the-resolution-of-packing-problems-using-simulated-annealing-and-genetic-algorithms/
@article{{}{.}, author = {Gomez, A., de la Fuente, D., Puente, J., Parreño, J.}, title = {The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms}, journal = {Strojniški vestnik - Journal of Mechanical Engineering}, volume = {51}, number = {5}, year = {2005}, doi = {}, url = {https://www.sv-jme.eu/sl/article/the-resolution-of-packing-problems-using-simulated-annealing-and-genetic-algorithms/} }
TY - JOUR AU - Gomez, Alberto AU - de la Fuente, David AU - Puente, Javier AU - Parreño, José PY - 2017/08/18 TI - The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 51, No 5 (2005): Strojniški vestnik - Journal of Mechanical Engineering DO - KW - genetic algorithms, packing, cutting processes, process optimization, N2 - The aim of this paper is to present two algorithms that are designed to optimise the cutting process of an L-type guillotine and to minimise the number of sheets used to manufacture a number of rectangular pieces. Two algorithms are proposed, one based on genetic algorithms and the other on simulated annealing. They are compared with the help of a bank of examples. Both algorithms provide very good results, although each of them has its peculiarities, which are described in this paper. UR - https://www.sv-jme.eu/sl/article/the-resolution-of-packing-problems-using-simulated-annealing-and-genetic-algorithms/
Gomez, Alberto, de la Fuente, David, Puente, Javier, AND Parreño, José. "The Resolution of Packing Problems Using Simulated Annealing and Genetic Algorithms" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 51 Number 5 (18 August 2017)
Strojniški vestnik - Journal of Mechanical Engineering 51(2005)5, 234-239
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
The aim of this paper is to present two algorithms that are designed to optimise the cutting process of an L-type guillotine and to minimise the number of sheets used to manufacture a number of rectangular pieces. Two algorithms are proposed, one based on genetic algorithms and the other on simulated annealing. They are compared with the help of a bank of examples. Both algorithms provide very good results, although each of them has its peculiarities, which are described in this paper.