TY - GEN
T1 - Parallel, multistage model for enterprise system of systems
AU - Kim, Harrison
AU - Lu, Shen
AU - Kim, Jin Suk
AU - Kim, Byoung Do
PY - 2008
Y1 - 2008
N2 - This paper describes a parallel, multistage optimization approach to enterprise system design and operations where a system design is linked with system operations (e.g., resource allocation) along the multistage decision making horizon. Our approach is composed of two parts: multistage formulation, and task-parallel algorithm. The formulation utilizes the quasi-separability of the multistage decision making structure, i.e., allowing relaxation by defining the linking variables for adjacent stages of decision making. The task-parallel algorithm enables optimal load balancing of the tasks and it is validated in the demonstration case where an airline plans to introduce multiple new aircraft to capture dynamically changing travel demand. Due to the complexity added onto the upcoming future stages in the optimization processes, a linearly increasing computational load is assumed as the number of stages increases. By utilizing this linearity, the proposed task- parallel algorithm demonstrates significant speedups and parallel performances.
AB - This paper describes a parallel, multistage optimization approach to enterprise system design and operations where a system design is linked with system operations (e.g., resource allocation) along the multistage decision making horizon. Our approach is composed of two parts: multistage formulation, and task-parallel algorithm. The formulation utilizes the quasi-separability of the multistage decision making structure, i.e., allowing relaxation by defining the linking variables for adjacent stages of decision making. The task-parallel algorithm enables optimal load balancing of the tasks and it is validated in the demonstration case where an airline plans to introduce multiple new aircraft to capture dynamically changing travel demand. Due to the complexity added onto the upcoming future stages in the optimization processes, a linearly increasing computational load is assumed as the number of stages increases. By utilizing this linearity, the proposed task- parallel algorithm demonstrates significant speedups and parallel performances.
UR - http://www.scopus.com/inward/record.url?scp=61449262972&partnerID=8YFLogxK
U2 - 10.1109/SYSOSE.2008.4724158
DO - 10.1109/SYSOSE.2008.4724158
M3 - Conference contribution
AN - SCOPUS:61449262972
SN - 9781424421732
T3 - 2008 IEEE International Conference on System of Systems Engineering, SoSE 2008
BT - 2008 IEEE International Conference on System of Systems Engineering, SoSE 2008
T2 - 2008 IEEE International Conference on System of Systems Engineering, SoSE 2008
Y2 - 2 June 2008 through 4 June 2008
ER -