TY - GEN

T1 - A simulated annealing algorithm for extended cell assignment problem in a wireless ATM network

AU - Din, Der Rong

PY - 2001/1/1

Y1 - 2001/1/1

N2 - In this paper, we investigate the extended cell assignment problem which optimally assigns new adding and splitting cells in PCS (Personal Communication Service) to switches in a wireless ATM (Asynchronous Transfer Mode) network. Given cells in a PCS and switches on an ATM network (whose locations are fixed and known), we would like to do the assignment in an attempt to minimize a cost criterion. The cost has two components: one is the cost of handoffs that involve two switches, and the other is the cost of cabling. This problem is modeled as a complex integer programming problem, and finding an optimal solution to this problem is NP-hard. A simulated annealing algorithm are proposed to solve this problem. The simulated annealing algorithm, ESA (enhanced simulated annealing), generates constraint-satisfy configurations, and uses three configuration perturbation schemes to change current configuration to a new one. Experimental results indicate that ESA algorithm has good performances.

AB - In this paper, we investigate the extended cell assignment problem which optimally assigns new adding and splitting cells in PCS (Personal Communication Service) to switches in a wireless ATM (Asynchronous Transfer Mode) network. Given cells in a PCS and switches on an ATM network (whose locations are fixed and known), we would like to do the assignment in an attempt to minimize a cost criterion. The cost has two components: one is the cost of handoffs that involve two switches, and the other is the cost of cabling. This problem is modeled as a complex integer programming problem, and finding an optimal solution to this problem is NP-hard. A simulated annealing algorithm are proposed to solve this problem. The simulated annealing algorithm, ESA (enhanced simulated annealing), generates constraint-satisfy configurations, and uses three configuration perturbation schemes to change current configuration to a new one. Experimental results indicate that ESA algorithm has good performances.

UR - http://www.scopus.com/inward/record.url?scp=84958044073&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84958044073&partnerID=8YFLogxK

U2 - 10.1007/3-540-45365-2_16

DO - 10.1007/3-540-45365-2_16

M3 - Conference contribution

AN - SCOPUS:84958044073

SN - 3540419209

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 150

EP - 159

BT - Applications of Evolutionary Computing - EvoWorkshops 2001

A2 - Boers, Egbert J. W.

PB - Springer Verlag

T2 - European Workshop Applications of Evolutionary Computing, EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM

Y2 - 18 April 2001 through 20 April 2001

ER -