Dantzig Type Optimization Method with Applications to Portfolio Selection

Park, Seyoung; Lee, Eun Ryung; Lee, Sungchul; Kim, Geonwoo

doi:10.3390/su11113216

Cited by 3 publications

(3 citation statements)

References 66 publications

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“…Bai et al [9] combined QFD theory with portfolio problems, defined the synergy function and fit ratio, and subsequently proposed a portfolio selection model based on strategic proximity. Park et al [10] divided operational investment projects into three types (sparse, sustainable, and stable projects) and constructed a balanced portfolio model of these three types of projects. However, the existing literature has yet to consider the scenario where the portfolio encompasses a franchise period and bears the responsibility of providing public services.…”

Section: Project Portfolio Selectionmentioning

confidence: 99%

“…Equation (11) denotes the allocation of a sufficient fee to meet both the construction expenses for the projects to be built and the operating expenses for the projects already completed at each stage. By combining Equations ( 8)- (10), the stage investment constraint Equation ( 11) can be constructed through recursive reasoning:…”

Section: Model Formulation and Constraintsmentioning

confidence: 99%

“…Equation (1) is the project completion constraint, indicating that if a project is selected, it must be completed within the entire investment period [8,12]; Equation ( 2) is the constraint on the number of executable projects in the entire investment period, and each period is determined by the organizational capacity of the enterprise [10]; Equation ( 4) is the nonrenewable resource constraint [13]; Equation ( 5) is the renewable resource constraint; Equation ( 7) is the 0-1 constraint of the corresponding decision variables [16].…”

Section: Model Formulation and Constraintsmentioning

confidence: 99%

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Project Portfolio Selection Considering the Fuzzy Chance Constraint of Water Environmental Restoration

Feng

et al. 2023

Water

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The water environment restoration project portfolio (WERP) selection is discussed in this paper. By complying with the analysis of the project’s multidimensional property and operation mode, this paper develops the chance constraint and the management constraint of the WERP from the perspectives of public service and enterprise operation. In addition, the multi-objective mixed integer linear programming model is constructed by combining the expectation method and the fuzzy chance constraint programming method. The results demonstrate that: (1) Our proposed method successfully circumvents the occurrence of local objective optimization within a specific confidence interval, thereby achieving a balance between economic and water environment restoration objectives; (2) including fuzzy chance constraints in our proposed method significantly diminishes the risk of exceeding the WERP capacity, thereby ensuring the effectiveness of water environment restoration by adopting a market-based approach. However, further examination of the impact of various sub-projects in WERP is necessary, along with the integration of novel evolutionary algorithms to enhance the efficiency of our model.

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Section: Project Portfolio Selectionmentioning

confidence: 99%

Section: Model Formulation and Constraintsmentioning

confidence: 99%

Section: Model Formulation and Constraintsmentioning

confidence: 99%

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Project Portfolio Selection Considering the Fuzzy Chance Constraint of Water Environmental Restoration

Feng

et al. 2023

Water

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A Systematic Literature Review on Quadratic Programming

Yagi¹,

Quiroz²,

Lengua³

2022

Proceedings of Seventh International Congress on Information and Communication Technology

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Explicit Value at Risk Goal Function in Bi-Level Portfolio Problem for Financial Sustainability

2021

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The mean-variance (MV) portfolio optimization targets higher return for investment period despite the unknown stochastic behavior of the future asset returns. That is why a risk is explicitly considering, quantified by algebraic characteristics of volatilities and co-variances. A new probabilistic definition of portfolio risk is the Value at Risk (VaR). The paper makes explicit inclusion and minimization of VaR as a quantitative measure of financial sustainability of a portfolio problem. Thus, the portfolio weights as problem solutions will respect not only the MV requirements for risk and return, but also the additional minimization of risk defined by VaR level. The portfolio problem is defined in a new, bi-level form. The upper level minimizes and evaluates the VaR value. The lower level evaluates the optimal assets weights by minimizing portfolio risk and maximizing the return in MV form. The bi-level model allows to have extended set of portfolio solutions with the portfolio weights and the value of VaR. Graphical interpretation of this bi-level definition of the portfolio problem explains the differences with the MV portfolio definition. Thus, the bi-level portfolio problem evaluates the optimal weights, which makes maximization of portfolio return and minimization of the risk in its algebraic and probabilistic form of definition.

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Dantzig Type Optimization Method with Applications to Portfolio Selection

Cited by 3 publications

References 66 publications

Project Portfolio Selection Considering the Fuzzy Chance Constraint of Water Environmental Restoration

Project Portfolio Selection Considering the Fuzzy Chance Constraint of Water Environmental Restoration

A Systematic Literature Review on Quadratic Programming

Explicit Value at Risk Goal Function in Bi-Level Portfolio Problem for Financial Sustainability

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