TY - GEN
T1 - Staged-deployment optimization for expansion planning of large scale complex systems
AU - Hamdan, Bayan
AU - Ho, Koki
AU - Wang, Pingfeng
N1 - Funding Information:
This research is partially supported by the National Science Foundation through the Faculty Early Career Development (CAREER) award (CMMI-1351414), and the NSF award (CMMI-1538508).
Publisher Copyright:
© 2019, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2019
Y1 - 2019
N2 - The needs of staged-deployment optimization for the expansion planning of large scale complex systems have been acknowledged extensively in various contexts. The design methods for adaptability or evolvability and their valuation have also been studied from both qualitative and quantitative perspectives. The flexibility gained by incorporating evolutionary design options has been analyzed using real options in projects and architecture options. Real options literature has typically tackled the flexible design problem by discretizing the time-variant uncertainties into scenarios and consider the flexible decision variables in each scenario separately. Given the discretized scenarios, stochastic optimization with either direct formulation or decision-rule based formulation, can be used to find the flexible designs. The importance of considering staged decisions is studied and the benefit of the model is evaluated in cases where the stochasticity of the parameters decreases with time. The impact of considering staged deployment for highly stochastic, large scale systems is investigated through a numerical case study. The case study presented in this paper investigates a multidisciplinary design problem that is typical in expansion planning for large scale complex systems. The importance of considering staged deployment for multi-disciplinary systems that have decreasing variability of their parameters with time is highlighted and demonstrated through the results of a numerical case study.
AB - The needs of staged-deployment optimization for the expansion planning of large scale complex systems have been acknowledged extensively in various contexts. The design methods for adaptability or evolvability and their valuation have also been studied from both qualitative and quantitative perspectives. The flexibility gained by incorporating evolutionary design options has been analyzed using real options in projects and architecture options. Real options literature has typically tackled the flexible design problem by discretizing the time-variant uncertainties into scenarios and consider the flexible decision variables in each scenario separately. Given the discretized scenarios, stochastic optimization with either direct formulation or decision-rule based formulation, can be used to find the flexible designs. The importance of considering staged decisions is studied and the benefit of the model is evaluated in cases where the stochasticity of the parameters decreases with time. The impact of considering staged deployment for highly stochastic, large scale systems is investigated through a numerical case study. The case study presented in this paper investigates a multidisciplinary design problem that is typical in expansion planning for large scale complex systems. The importance of considering staged deployment for multi-disciplinary systems that have decreasing variability of their parameters with time is highlighted and demonstrated through the results of a numerical case study.
UR - http://www.scopus.com/inward/record.url?scp=85083944522&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85083944522&partnerID=8YFLogxK
U2 - 10.2514/6.2019-2217
DO - 10.2514/6.2019-2217
M3 - Conference contribution
AN - SCOPUS:85083944522
SN - 9781624105784
T3 - AIAA Scitech 2019 Forum
BT - AIAA Scitech 2019 Forum
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
T2 - AIAA Scitech Forum, 2019
Y2 - 7 January 2019 through 11 January 2019
ER -