A robust goal programming model for the capital budgeting problem

Bojd, Fatemeh Ghasemi; Koosha, Hamidreza

doi:10.1080/01605682.2017.1389673

Cited by 12 publications

(8 citation statements)

References 37 publications

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“…O orçamento de capital é um mecanismo de planejamento usado por uma organização para tomar decisões de avaliação sobre como alocar recursos entre projetos de investimento (Bojd & Koosha, 2018). Práticas de orçamento de capital são técnicas e métodos que ajudam a identificar a viabilidade projeto (Al-Mutairi, Naser & Saeid, 2018).…”

Section: Práticas De Análise De Investimentosunclassified

Associação Entre Características Do Top Management Team (Tmt) E Utilização De Práticas De Análise De Investimentos

Michelon¹,

Mendes

Lunkes

et al. 2021

Contab. Vista & Rev.

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Este estudo se destina a analisar a associação entre idade, participação de mulheres e nível educacional do Top Management Team (TMT) e utilização das práticas de análise de investimentos. Para a coleta dos dados, aplicou-se um questionário nas empresas da Brasil, Bolsa, Balcão (B3), com a obtenção de 94 respostas. Para a análise dos dados, utilizou-se associação entre variáveis categóricas por homogeneidade (HOMALS). Os resultados indicam que as práticas tradicionais e sofisticadas são mais utilizadas à medida que a idade média da equipe de gestão aumenta. A participação de mulheres na equipe de gestão tem maior associação com a não utilização das práticas sofisticadas de análise de investimento. As associações do nível educacional não apresentaram uma tendência claramente definida para a característica. Este estudo contribui para a literatura da Teoria dos Escalões Superiores (TES) e de práticas de análise de investimentos, fornecendo novas evidências sobre a associação entre as características dos gestores de alto escalão e a utilização das práticas.

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Section: Práticas De Análise De Investimentosunclassified

Associação Entre Características Do Top Management Team (Tmt) E Utilização De Práticas De Análise De Investimentos

Michelon¹,

Mendes

Lunkes

et al. 2021

Contab. Vista & Rev.

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show abstract

“…This is apparent since the robustness of both models is obtained through cardinality-constraints via interval uncertainty. On the contrary, while model (19)-(23) imposes a total penalty of j∈G t p tj + k t z t for the variability in each goal, model (19)-(23) identifies a total goal-specific penalty p t through every combination of δ tj x j in some given k t , as indicated in Constraint (21). Observe that Constraint (21) applies L 1 -norm uncertainty sets to the possible set of coefficient subject to parametric uncertainty (i.e., S t ∈ J t , |S t | = k t , q ∈ J t \S t , t ∈ T).…”

Section: Hanks Et Al's Rgp Approachmentioning

confidence: 99%

“…for the variability in each goal, model (19)-(23) identifies a total goal-specific penalty through every combination of in some given , as indicated in Constraint (21). Observe that Constraint (21) applies -norm uncertainty sets to the possible set of coefficient subject to parametric uncertainty (i.e., ∈ , | | = , ∈ \ , ∈ ).…”

Section: Lrgp Via Ellipsoidal Uncertainty Setmentioning

confidence: 99%

“…The RGP was first introduced by [19], and its potential use in multi-criteria linear programming problems is discussed in [20]. RGP has been applied, for example, to the multi-objective portfolio selection problem in [16], the capital budgeting problem in [21], and a transportation problem, specifically, the United States Transportation Command's (USTRANSCOM) liner rate-setting problem in [22]. Despite this, the RGP methodology remains underdeveloped and less applied, specifically when considering different robust concepts and variants of GP techniques.…”

Section: Introductionmentioning

confidence: 99%

“…Contrary to the conservative models provided in the literature (c.f., [13,16,19,21,22]), we present LRGP models generalized to two arbitrary sets-the budget of uncertainty and the ellipsoidal uncertainty set. The model formulation made with these uncertainty sets provides robust solutions among those which are "not too far" from optimality for the nominal GP model.…”

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confidence: 99%

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Light Robust Goal Programming

Mensah

Rocca

2019

MCA

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Robust goal programming (RGP) is an emerging field of research in decision-making problems with multiple conflicting objectives and uncertain parameters. RGP combines robust optimization (RO) with variants of goal programming techniques to achieve stable and reliable goals for previously unspecified aspiration levels of the decision-maker. The RGP model proposed in Kuchta (2004) and recently advanced in Hanks, Weir, and Lunday (2017) uses classical robust methods. The drawback of these methods is that they can produce optimal values far from the optimal value of the “nominal” problem. As a proposal for overcoming the aforementioned drawback, we propose light RGP models generalized for the budget of uncertainty and ellipsoidal uncertainty sets in the framework discussed in Schöbel (2014) and compare them with the previous RGP models. Conclusions regarding the use of different uncertainty sets for the light RGP are made. Most importantly, we discuss that the total goal deviations of the decision-maker are very much dependent on the threshold set rather than the type of uncertainty set used.

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A Robust Weighted Goal Programming Approach for Supplier Selection Problem with Inventory Management and Vehicle Allocation in Uncertain Environment

Wang

2019

Advances in Intelligent Systems and Computing

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A robust goal programming model for the capital budgeting problem

Cited by 12 publications

References 37 publications

Associação Entre Características Do Top Management Team (Tmt) E Utilização De Práticas De Análise De Investimentos

Associação Entre Características Do Top Management Team (Tmt) E Utilização De Práticas De Análise De Investimentos

Light Robust Goal Programming

A Robust Weighted Goal Programming Approach for Supplier Selection Problem with Inventory Management and Vehicle Allocation in Uncertain Environment

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