Multiobjective credibilistic portfolio selection model with fuzzy chance-constraints

Gupta, Pankaj; Inuiguchi, Masahiro; Mehlawat, Mukesh Kumar; Mittal, Garima

doi:10.1016/j.ins.2012.12.011

Cited by 65 publications

(35 citation statements)

References 41 publications

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“…Then, the project evaluation approach is applied in a case study of a gas and oil development holding firm to evaluate its R&D project proposals. To illustrate the effectiveness of the introduced model under larger data sets after careful review of the studies in the existing literature (e.g., [27,67]), a data set consisting of 20 candidate projects has been made and adopted to be used in the proposed project portfolio selection process. Eventually, the managerial implications of applying model in the provided case study are presented.…”

Section: Applications Of Proposed Interval Type-2 Fuzzy Optimization mentioning

confidence: 99%

R&D project evaluation and project portfolio selection by a new interval type-2 fuzzy optimization approach

Mohagheghi

Mousavi

Vahdani

et al. 2016

Neural Comput & Applic

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In today's ever-changing and highly uncertain environment, organizations depend on research and development (R&D) activities to adapt intensive growth of technology. One of the most important and trickiest tasks of any developing firms is to define new projects. This process gets difficult when it comes to choosing an appropriate portfolio from a set of candidate projects. Since organizations are faced with limited resources of R&D and budget constraints, they have to choose a project portfolio that mitigates the corresponding risk and enhances the overall value of portfolio. Therefore, the purpose of this study is to introduce a practical model to select the best and the most proper project portfolio while considering project investment capital, return rate, and risk. The ever-changing and highly uncertain environment of projects is addressed by utilizing interval type-2 fuzzy sets (IT2FSs). In this paper, a new model of R&D project evaluation is first introduced. This model includes a new risk-return index. This model is then extended in project portfolio selection, and as a result, a new model of R&D project portfolio selection is proposed under uncertainty. Constraints and limitations of R&D project portfolio selection are comprehensively addressed. In this model, lower semi-variance is applied to consider risk of proposed projects. Therefore, this paper offers a new model that applies IT2FSs to handle uncertainty, uses semi-variance to assess risk, synchronously considers risk and return in its selection process, and addresses the considerations and limits of realworld problems. Eventually, to verify the proposed model, a numerical example of the existing literature is solved with the model, and the results are compared. The first proposed model is used to prioritize proposed R&D projects of a gas and oil development holding firm as a real case study. To illustrate further, a practical example is also provided to demonstrate the applicability of the proposed project portfolio selection model.

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Section: Applications Of Proposed Interval Type-2 Fuzzy Optimization mentioning

confidence: 99%

R&D project evaluation and project portfolio selection by a new interval type-2 fuzzy optimization approach

Mohagheghi

Mousavi

Vahdani

et al. 2016

Neural Comput & Applic

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“…In most recent studies, some people focused on developing hybrid methodologies of two mentioned directions. Gupta et al (2013) proposed a multiobjective credibilistic model with fuzzy chance constraints of the portfolio selection problem. The problem was solved using a hybrid intelligent algorithm that integrates fuzzy simulation with a real-coded genetic algorithm.…”

Section: Introductionmentioning

confidence: 99%

A multi period portfolio selection using chance constrained programming

Hassanlou¹

2017

10.5267/j.dsl

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This paper considers a portfolio selection problem with normally distributed returns and different rates for borrowing and lending. The primary concern is to determine the amount of investment in different planning horizons when the rate of borrowing is greater than the rate of lending. Chance constrained programming as an appropriate tool for addressing intrinsic uncertainty in portfolio selection problem is used. To solve this nonlinear programming, Genetic Algorithm is utilized. Numerical experiments are performed and the results are analyzed to present the performance of the proposed methodology.Growing Science Ltd. All rights reserved. 7

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“…have been used to solve extended portfolio selection models (e.g. [4,17,29,[30][31][32][33][34][35][36]). …”

Section: Introductionmentioning

confidence: 99%

An integrated multi-objective Markowitz–DEA cross-efficiency model with fuzzy returns for portfolio selection problem

Mashayekhi

Omrani

2016

Applied Soft Computing

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Multiobjective credibilistic portfolio selection model with fuzzy chance-constraints

Cited by 65 publications

References 41 publications

R&D project evaluation and project portfolio selection by a new interval type-2 fuzzy optimization approach

R&D project evaluation and project portfolio selection by a new interval type-2 fuzzy optimization approach

A multi period portfolio selection using chance constrained programming

An integrated multi-objective Markowitz–DEA cross-efficiency model with fuzzy returns for portfolio selection problem

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