A System of Systems Approach for Effects-Based Operational Planning Under Uncertainty

被引:1
|
作者
McInvale, Howard D. [1 ]
McDonald, Mark P.
Mahadevan, Sankaran [2 ]
机构
[1] US Mil Acad, West Point, NY 10996 USA
[2] Vanderbilt Univ, NSF IGERT Multidisciplinary Doctoral Program Reli, Nashville, TN 37235 USA
基金
美国国家科学基金会;
关键词
RELIABILITY; OPTIMIZATION; DESIGN;
D O I
10.5711/1082598316333
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Operational planning under uncertainty is often difficult because assessment of the impacts of these operations often requires a system of systems (SoS) level analysis to guide decision making. For example, one objective for military and support operations undertaken in Iraq and Afghanistan is to restore economic productivity in order to promote social order and stability. Yet, planning in this context is challenging due to the highly interdependent nature of the economic sectors. This paper develops a framework for decision support in effects-based operations (EBO) planning that integrates systems modeling, uncertainty analysis, and optimization. The proposed optimization under uncertainty (OUU) framework has three components that: 1) represent a network of interdependent systems using input-output models that describe the behavior of the various systems; 2) analyze and propagate uncertainties using analytical reliability methods; and 3) optimize SoS-level objectives under these uncertainties. Optimality conditions are derived for the proposed optimization formulation. A solution algorithm is presented and illustrated using numerical data representative of a predominantly oil-based national economy.
引用
收藏
页码:33 / 48
页数:16
相关论文
共 50 条
  • [1] Using Genetic Algorithms in Effects-based Planning
    Younas, Irfan
    Ayani, Rassul
    Schubert, Johan
    Asadi, Hirad
    2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013), 2013, : 438 - 443
  • [2] Tactical and Operational Planning of Multirefinery Networks under Uncertainty: An Iterative Integration Approach
    Leiras, Adriana
    Ribas, Gabriela
    Hamacher, Silvio
    Elkamel, Ali
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2013, 52 (25) : 8507 - 8517
  • [3] Operational harvest planning under forest road maintenance uncertainty
    Gomes, Vanessa de Souza
    Monti, Cassio Augusto Ussi
    Silva, Carolina Souza Jarochinski e
    Gomide, Lucas Rezende
    FOREST POLICY AND ECONOMICS, 2021, 131
  • [4] Operational Planning of Hydrothermal Systems Based on a Fuzzy-PSO Approach
    Rabelo, Ricardo A. L.
    Fernandes, Ricardo A. S.
    Silva, Ivan N.
    2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2012,
  • [5] Integrating operational decisions into the planning of one-way vehicle-sharing systems under uncertainty
    Deng, Yinghan
    Cardin, Michel-Alexandre
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 86 : 407 - 424
  • [6] An Operational Scheduling Framework for Tanker-Based Water Distribution Systems under Uncertainty
    Maheshwari, Abhilasha
    Misra, Shamik
    Gudi, Ravindra
    Subbiah, Senthilmurugan
    Laspidou, Chrysi
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2023, 62 (27) : 10523 - 10541
  • [7] Factorial Based Stochastic Optimization Approach for Energy and Environmental Systems Management Under Uncertainty
    Liu, Zhengping
    Huang, Guohe
    Wu, Chuanbao
    Ji, Ling
    Niu, Dongxiao
    ENVIRONMENTAL ENGINEERING SCIENCE, 2017, 34 (07) : 469 - 480
  • [8] Optimal Bilevel Model for Stochastic Risk-Based Planning of Microgrids Under Uncertainty
    Gazijahani, Farhad Samadi
    Salehi, Javad
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 14 (07) : 3054 - 3064
  • [9] Planning low-carbon electricity systems under uncertainty considering operational flexibility and smart grid technologies
    Moreno, Rodrigo
    Street, Alexandre
    Arroyo, Jose M.
    Mancarella, Pierluigi
    PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2017, 375 (2100):
  • [10] Collaborative effects-based planning using adversary models and target set optimization
    Pioch, NJ
    Daniels, T
    Pielech, B
    ENABLING TECHNOLOGIES FOR SIMULATION SCIENCE VIII, 2004, 5423 : 399 - 410