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A Multi-Objective Risk-Based Framework For Mission Capability Planning

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  • LAM T. BUI

    ()
    (School of ITEE, UNSW@ADFA, University of New South Wales, NorthCott Drive, Canberra, ACT, Australia, 2600, Australia)

  • MICHAEL BARLOW

    ()
    (School of ITEE, UNSW@ADFA, University of New South Wales, NorthCott Drive, Canberra, ACT, Australia, 2600, Australia)

  • HUSSEIN A. ABBASS

    ()
    (School of ITEE, UNSW@ADFA, University of New South Wales, NorthCott Drive, Canberra, ACT, Australia, 2600, Australia)

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    Abstract

    In this paper, we propose a risk-based framework for military capability planning. Within this framework, metaheuristic techniques such as Evolutionary Algorithms are used to deal with multi-objectivity of a class of NP-hard resource investment problems, called The Mission Capability Planning Problem, under the presence of risk factors. This problem inherently has at least two conflicting objectives: minimizing the cost of investment in the resources as well as the makespan of the plans. The framework allows the addition of a risk-based objective to the problem in order to support risk assessment during the planning process. In other words, with this framework, a mechanism of progressive risk assessment is introduced to capability planning.We analyze the performance of the proposed framework under both scenarios: with and without risk. In the case of no risk, the purpose is to study several optimization-related aspects of the framework such as convergence, trade-off analysis, and its sensitivity to the algorithm parameters; while the second case is to demonstrate the ability of the framework in supporting risk assessment and also robustness analysis.

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    Bibliographic Info

    Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal New Mathematics and Natural Computation.

    Volume (Year): 05 (2009)
    Issue (Month): 02 ()
    Pages: 459-485

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    Handle: RePEc:wsi:nmncxx:v:05:y:2009:i:02:p:459-485

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    Related research

    Keywords: Risk analysis; military mission; capabilities; planning; evolutionary algorithms; multi-objective;

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