Sustainable project portfolio selection and optimization with considerations of outsourcing decisions, financing options and staff assignment under interval type-2 fuzzy uncertainty

Mohagheghi, Vahid; Mousavi, Seyed Meysam; Shahabi-Shahmiri, Reza

doi:10.1007/s00521-022-07207-3

Cited by 9 publications

(3 citation statements)

References 50 publications

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“…Future research endeavors can build upon these foundations to further enhance the contractor selection process and integrate new technologies for improved decision-making capabilities. In addition, to handle high uncertainty in the real-world applications, new extended fuzzy sets, such as type-2 fuzzy sets, interval-valued intuitionistic fuzzy sets, and interval-valued Pythagorean fuzzy sets, can be taken from the recent literature [44][45][46][47][48][49][50].…”

Section: Discussionmentioning

confidence: 99%

Enhancing Contractor Selection Process by a New Interval-Valued Fuzzy Decision-Making Model Based on SWARA and CoCoSo Methods

Karami

Mousavi

Antuchevičienė

2023

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Contractor selection is a crucial aspect of construction projects, with a significant impact on project success. However, traditional methods may not effectively handle the complexities and uncertainties involved in decision-making. To address this, advanced techniques like Multi-Criteria Decision-Making (MCDM) have been developed. In this study, we propose a new approach based on two uncertain methods, Interval-Valued Fuzzy Step-Wise Weight Assessment Ratio Analysis (IVF-SWARA) and Interval-Valued Fuzzy Combined Compromise Solution (IVF-CoCoSo), for contractor selection in construction projects. These methods use interval-valued fuzzy numbers (IVFNs) to handle decision-making under uncertainty and imprecision. By leveraging the benefits of IVFNs, the proposed methods enhance accuracy and flexibility, enabling more informed and reliable decisions. An application example illustrates the effectiveness of the methods, and sensitivity analysis examines how varying criteria weights affect contractor rankings. The study concludes that the IVF-SWARA and IVF-CoCoSo methods assist decision-makers in selecting suitable contractors and achieving project success. These methods provide a robust framework to navigate complexities and uncertainties, leading to improved decision-making in contractor selection for construction projects.

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Section: Discussionmentioning

confidence: 99%

Enhancing Contractor Selection Process by a New Interval-Valued Fuzzy Decision-Making Model Based on SWARA and CoCoSo Methods

Karami

Mousavi

Antuchevičienė

2023

Axioms

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“…Considering the effect of the quality reduction of predecessor activities on the quality of the subsequent activities in the quality objective function equation can improve it. In order to better regard high uncertainty in the real-world, extended fuzzy sets, such as type-2 fuzzy sets, can be applied from the related literature [44][45][46][47]. To improve the results, a new approach for determining the weight of each project activity can be developed.…”

Section: Discussionmentioning

confidence: 99%

A Mathematical Model and Two Fuzzy Approaches Based on Credibility and Expected Interval for Project Cost-Quality-Risk Trade-Off Problem in Time-Constrained Conditions

Haghighi

Mousavi

2022

Algorithms

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To successfully finalize projects and attain their determined purposes, it is indispensable to control all success criteria of a project. The time–cost trade-off (TCT) is known as a prevalent and efficient approach applied when the planned finish date of a project is not admitted by stakeholders, and consequently, the project duration must be decreased. This paper proposes a new mathematical model under fuzzy uncertainty to deal with the project cost–risk–quality trade-off problem (CRQT) under time constraints. Because of the unique nature of projects and their uncertain circumstances, applying crisp values for some project parameters does not seem appropriate. Hence, this paper employs fuzzy sets to resolve these weaknesses. In this study, two approaches are presented to handle proposed fuzzy multi-objective mathematical model. First, fuzzy credibility theory and then goal attainment method are used. Secondly, the model is solved by a fuzzy method based on expected interval and value and augmented ɛ-constraint method. A project from the literature review is adopted and solved by the presented methodology. The results demonstrate the accuracy and efficiency of the two proposed approaches for the introduced practical problem.

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“…Imprecise information can be handled in various ways. Among them, probability and fuzzy sets (FSs) theories are popular approaches to address incomplete information [42][43][44][45]. In this respect, the robust possibilistic programming approach [40] was utilized to decrease the variation of parameters in the biofuel supply chain environment.…”

Section: Solution Approachmentioning

confidence: 99%

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

et al. 2022

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In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO2 emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO2 emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model.

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Sustainable project portfolio selection and optimization with considerations of outsourcing decisions, financing options and staff assignment under interval type-2 fuzzy uncertainty

Cited by 9 publications

References 50 publications

Enhancing Contractor Selection Process by a New Interval-Valued Fuzzy Decision-Making Model Based on SWARA and CoCoSo Methods

Enhancing Contractor Selection Process by a New Interval-Valued Fuzzy Decision-Making Model Based on SWARA and CoCoSo Methods

A Mathematical Model and Two Fuzzy Approaches Based on Credibility and Expected Interval for Project Cost-Quality-Risk Trade-Off Problem in Time-Constrained Conditions

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

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