TY - GEN
T1 - A novel hybrid ACO/SA approach to solve Stochastic Dynamic Facility Layout Problem (SDFLP)
AU - Lee, T. S.
AU - Moslemipour, Ghorbanali
AU - Ting, T. O.
AU - Rilling, Dirk
PY - 2012
Y1 - 2012
N2 - This paper proposes a new hybrid algorithm using ant colony optimization and simulated annealing intelligent approaches to solve a stochastic dynamic facility layout problem in which product demands are normally distributed random variables with known probability density function that changes from period to period in a random manner. Finally, the performance of the proposed algorithm is compared with the simulated annealing and another approach using data taken from the literature.
AB - This paper proposes a new hybrid algorithm using ant colony optimization and simulated annealing intelligent approaches to solve a stochastic dynamic facility layout problem in which product demands are normally distributed random variables with known probability density function that changes from period to period in a random manner. Finally, the performance of the proposed algorithm is compared with the simulated annealing and another approach using data taken from the literature.
KW - Ant colony optimization
KW - dynamic layout problem
KW - simulated annealing
KW - stochastic environment
UR - https://www.scopus.com/pages/publications/84865022764
U2 - 10.1007/978-3-642-31837-5_15
DO - 10.1007/978-3-642-31837-5_15
M3 - Conference Proceeding
AN - SCOPUS:84865022764
SN - 9783642318368
T3 - Communications in Computer and Information Science
SP - 100
EP - 108
BT - Emerging Intelligent Computing Technology and Applications - 8th International Conference, ICIC 2012, Proceedings
T2 - 8th International Conference on Emerging Intelligent Computing Technology and Applications, ICIC 2012
Y2 - 25 July 2012 through 29 July 2012
ER -