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Strategic positioning in tactical scenario planning

Published: 12 July 2008 Publication History

Abstract

Capability planning problems are pervasive throughout many areas of human interest with prominent examples found in defense and security. Planning provides a unique context for optimization that has not been explored in great detail and involves a number of interesting challenges which are distinct from traditional optimization research.
Planning problems demand solutions that can satisfy a number of competing objectives on multiple scales related to robustness, adaptiveness, risk, etc. The scenario method is a key approach for planning. Scenarios can be defined for long-term as well as short-term plans. This paper introduces computational scenario-based planning problems and proposes ways to accommodate strategic positioning within the tactical planning domain.
We demonstrate the methodology in a resource planning problem that is solved with a multi-objective evolutionary algorithm. Our discussion and results highlight the fact that scenario-based planning is naturally framed within a multi-objective setting. However, the conflicting objectives occur on different system levels rather than within a single system alone. This paper also contends that planning problems are of vital interest in many human endeavors and that Evolutionary Computation may be well positioned for this problem domain.

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Cited By

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  • (2020)Portfolio Optimization for Defence ApplicationsIEEE Access10.1109/ACCESS.2020.29831418(60152-60178)Online publication date: 2020
  • (2016)A multi-objective approach for weapon selection and planning problems in dynamic environmentsJournal of Industrial and Management Optimization10.3934/jimo.201606813:3(1189-1211)Online publication date: Oct-2016
  • (2009)Application notesIEEE Computational Intelligence Magazine10.1109/MCI.2009.9330984:3(29-36)Online publication date: 1-Aug-2009

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  1. Strategic positioning in tactical scenario planning

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    cover image ACM Conferences
    GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation
    July 2008
    1814 pages
    ISBN:9781605581309
    DOI:10.1145/1389095
    • Conference Chair:
    • Conor Ryan,
    • Editor:
    • Maarten Keijzer
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 12 July 2008

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    Author Tags

    1. decision support
    2. evolutionary algorithms
    3. military planning
    4. scenarios
    5. strategic planning
    6. uncertainty

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    Cited By

    View all
    • (2020)Portfolio Optimization for Defence ApplicationsIEEE Access10.1109/ACCESS.2020.29831418(60152-60178)Online publication date: 2020
    • (2016)A multi-objective approach for weapon selection and planning problems in dynamic environmentsJournal of Industrial and Management Optimization10.3934/jimo.201606813:3(1189-1211)Online publication date: Oct-2016
    • (2009)Application notesIEEE Computational Intelligence Magazine10.1109/MCI.2009.9330984:3(29-36)Online publication date: 1-Aug-2009

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