2012
DOI: 10.1002/sys.21212
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Budget‐constrained portfolio trades using multiobjective optimization

Abstract: A decision support process using many‐objective optimization, high‐performance computing, and advanced visualization is applied to gain comprehensive insight into multistakeholder portfolio budgeting trades. The key tradeoffs among nondominated portfolio budget solutions are systematically identified and examined with respect to different stakeholder viewpoints. The approach is illustrated using a portfolio of 14 U.S. Air Force satellite development programs using budget data taken from the 2010 Future Year De… Show more

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Cited by 15 publications
(13 citation statements)
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“…New multidimensional data exploration and visualization tools such as AeroVis (which can graphically display up to 7 dimensions of information) and custom MATLAB post-processing applications are employed to gain deep insights into complicated non-dominated trades involving a diverse group of stakeholders. (Smith et al, 2012) GRIPS integrates evolutionary computation paradigms (genetic programming, genetic algorithms, and multi-objective evolutionary algorithms). Multi-objective evolutionary algorithms have been shown to be effective optimization tools to search the complex tradeoff spaces of for example, satellite constellation design.…”
Section: Grips Analytic Enginementioning
confidence: 99%
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“…New multidimensional data exploration and visualization tools such as AeroVis (which can graphically display up to 7 dimensions of information) and custom MATLAB post-processing applications are employed to gain deep insights into complicated non-dominated trades involving a diverse group of stakeholders. (Smith et al, 2012) GRIPS integrates evolutionary computation paradigms (genetic programming, genetic algorithms, and multi-objective evolutionary algorithms). Multi-objective evolutionary algorithms have been shown to be effective optimization tools to search the complex tradeoff spaces of for example, satellite constellation design.…”
Section: Grips Analytic Enginementioning
confidence: 99%
“…In Figure 2, non-dominated solution set for maximizing design life and minimizing cost contains designs represented by points A, B, and C. The feasible objective space (grey region) also contains designs D and E which are referred to as dominated or inferior relative to A, B, and C. Figure 2. Example of Non-dominated solution Set (Smith et al, 2012) This is an essential facet of the decision support process, which ties together problem formulation, modeling, multi-objective optimization, and visual analytics into a recurring cycle, illustrated in Figure 3. The tool performs analysis of the problem formulation, wrapping the appropriate model into a framework for parallelized search and optimization using a multi-objective evolutionary algorithm.…”
Section: Grips Analytic Enginementioning
confidence: 99%
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“…A justificativa e relevância do presente estudo são baseadas em três itens: (1) na importância que o gerenciamento de portfólio de projetos tem para o desenvolvimento e aprimoramento do setor público (CRUZ-REYES et al, 2014DUARTE;REIS, 2006;RADNOR;NOKE, 2013); (2) na existência de uma lacuna de pesquisas sobre o tema devido à escassez de artigos, lacuna que é apontada, tanto sobre o gerenciamento de portfólio de projetos no setor público num aspecto amplo por Arlbjørn, Freytag e Thoms (2015), Hansen e Kraemmergaard (2013), Smith et al (2012) e Young et al (2012), quanto em um aspecto mais restrito, de áreas específicas, como em Tecnologia da Informação (TI) (NIELSEN; PEDERSEN, 2014) e energia (BAKER;SOLAK, 2014). Tal lacuna também foi identificada na revisão da literatura realizada como demonstrado no item 3 do presente trabalho; e (3) no fato do setor público ainda estar iniciando a adoção do uso do gerenciamento de portfólio (BAKER; SOLAK, 2014) e, portanto, seus resultados ainda levarão algum tempo para serem sentidos (PILKAITĖ;CHMIELIAUSKAS, 2015).…”
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