<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Formalizing the Optimization Problem in Long-Term Capability Planning</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">2009</style></number><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">99-114</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%"> In defining future force capabilities, decision makers need to balance objectives, strategy, force capabilities, and risk within a forecasted force develop­ment environment and resource levels. This is commonly a task in long-term de­fense and force planning. This paper presents a mathematical formalization of the planning problem that involves static and dynamic optimization. Several static and dynamic discrete optimization models illustrate the approach. The concluding sec­tion presents a short deliberation on applicability.
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