A fuzzy hybrid project portfolio selection method using Data Envelopment Analysis, TOPSIS and Integer Programming

Tavana, Madjid; Keramatpour, Mehdi; Santos‐Arteaga, Francisco J.; Ghorbaniane, Esmail

doi:10.1016/j.eswa.2015.06.057

Cited by 135 publications

(91 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Integer programming (IP) is a special type of linear program, which adds the attribute specification of integers to the optimization model [27][28][29]. It gradually evolved from the cutting plane method proposed by Gomory [30].…”

Section: Methodsmentioning

confidence: 99%

Application of a Double-Sided Chance-Constrained Integer Linear Program for Optimization of the Incremental Value of Ecosystem Services in Jilin Province, China

Cai

Wang

2017

Water

View full text Add to dashboard Cite

Abstract:The Interconnected River System Network Project (IRSNP) is a significant water supply engineering project, which is capable of effectively utilizing flood resources to generate ecological value, by connecting 198 lakes and ponds in western Jilin, northeast China. In this article, an optimization research approach has been proposed to maximize the incremental value of IRSNP ecosystem services. A double-sided chance-constrained integer linear program (DCCILP) method has been proposed to support the optimization, which can deal with uncertainties presented as integers or random parameters that appear on both sides of the decision variable at the same time. The optimal scheme indicates that after rational optimization, the total incremental value of ecosystem services from the interconnected river system network project increased 22.25%, providing an increase in benefits of 3.26 × 10 9 ¥ compared to the original scheme. Most of the functional area is swamp wetland, which provides the greatest ecological benefits. Adjustment services increased obviously, implying that the optimization scheme prioritizes ecological benefits rather than supply and production services.Keywords: incremental value of ecosystem service; double-sided chance-constrained integer linear program; interconnected river system network project; optimization; utilization of flood resource

show abstract

Section: Methodsmentioning

confidence: 99%

Application of a Double-Sided Chance-Constrained Integer Linear Program for Optimization of the Incremental Value of Ecosystem Services in Jilin Province, China

Cai

Wang

2017

Water

View full text Add to dashboard Cite

show abstract

“…Tavana et al [13] proposed a model consisting of three sections that is DEA, TOPSIS, and linear integer programming for the selection of an optimal project portfolio. In a fuzzy environment, Bolat et al [14] developed a systematic and comprehensive project selection model utilizing fuzzy multi-objective linear programming that could deal with imprecise data and the uncertain judgments of decision-makers.…”

Section: Mathematical Programming Methodsmentioning

confidence: 99%

“…Many mathematical programming methods have been adapted to create decision models for R&D project selection, including integer programming [13], linear programming [14], nonlinear programming [15], goal programming [16] and dynamic programming [17] techniques. Tavana et al [13] proposed a model consisting of three sections that is DEA, TOPSIS, and linear integer programming for the selection of an optimal project portfolio.…”

Section: Mathematical Programming Methodsmentioning

confidence: 99%

A Consistent Fuzzy Preference Relations Based ANP Model for R&D Project Selection

2017

View full text Add to dashboard Cite

In today's rapidly changing economy, technology companies have to make decisions on research and development (R&D) projects investment on a routine bases with such decisions having a direct impact on that company's profitability, sustainability and future growth. Companies seeking profitable opportunities for investment and project selection must consider many factors such as resource limitations and differences in assessment, with consideration of both qualitative and quantitative criteria. Often, differences in perception by the various stakeholders hinder the attainment of a consensus of opinion and coordination efforts. Thus, in this study, a hybrid model is developed for the consideration of the complex criteria taking into account the different opinions of the various stakeholders who often come from different departments within the company and have different opinions about which direction to take. The decision-making trial and evaluation laboratory (DEMATEL) approach is used to convert the cause and effect relations representing the criteria into a visual network structure. A consistent fuzzy preference relations based analytic network process (CFPR-ANP) method is developed to calculate the preference-weights of the criteria based on the derived network structure. The CFPR-ANP is an improvement over the original analytic network process (ANP) method in that it reduces the problem of inconsistency as well as the number of pairwise comparisons. The combined complex proportional assessment (COPRAS-G) method is applied with fuzzy grey relations to resolve conflicts arising from differences in information and opinions provided by the different stakeholders about the selection of the most suitable R&D projects. This novel combination approach is then used to assist an international brand-name company to prioritize projects and make project decisions that will maximize returns and ensure sustainability for the company.

show abstract

“…Project evaluation and selection processes need to consider multiple factors simultaneously so that researchers have led to apply multicriteria decision‐making methods (e.g., Amiri, ; Su & Chou, ). However, the specific requirements involved in complex project portfolio selection problems in real life may not be met by applying a multicriteria decision‐making sequence method alone (Tavana, Keramatpour, Santos‐Arteaga, & Ghorbaniane, ). Multistage methodologies including multicriteria decision‐making methods have been commonly used in the literature to address this problem more realistically (e.g., Ghasemzadeh & Archer, ; Lee & Kim, ; Mavrotas, Diakoulaki, & Capros, ).…”

Section: Introductionmentioning

confidence: 99%

A two‐stage fuzzy approach for Industry 4.0 project portfolio selection within criteria and project interdependencies context

Keskin

2019

Multi Criteria Decision Anal

View full text Add to dashboard Cite

Industry 4.0, the new vision of our age has forced companies to transform their processes. In the process of transition to Industry 4.0, one of the most crucial success factors is to select the project portfolio that best fits their objectives. The uncertainty included in the projects, the interproject priority, and various interdependence relations, interactions between project evaluation criteria, decision makers with different perspectives, and preferences make Industry 4.0 project portfolio selection decision considerably complicated. In this study, a two‐stage fuzzy approach is proposed to address this complex problem. In the first stage of the approach, the main criteria and subcriteria to be used in evaluating the Industry 4.0 projects have been determined based on the literature review and expert opinions. Following this, a network structure representing outer and inner dependencies has been formed, and the priority weights of the criteria have been obtained by taking into consideration these dependencies. Then, each of the project alternatives has been evaluated under subcriteria, and desirability indexes of project alternatives have been calculated. Fuzzy analytic network process has been applied in this stage. In the second stage, fuzzy multi‐objective nonlinear programming has been used to select a project portfolio. In the application of the first stage of the proposed methodology, experts from three firms, which have made significant progress in the Industry 4.0 implementation process, are the decision makers. In the application of the second stage, hypothetically created project alternatives and their dataset have been used.

show abstract

A fuzzy hybrid project portfolio selection method using Data Envelopment Analysis, TOPSIS and Integer Programming

Cited by 135 publications

References 32 publications

Application of a Double-Sided Chance-Constrained Integer Linear Program for Optimization of the Incremental Value of Ecosystem Services in Jilin Province, China

Application of a Double-Sided Chance-Constrained Integer Linear Program for Optimization of the Incremental Value of Ecosystem Services in Jilin Province, China

A Consistent Fuzzy Preference Relations Based ANP Model for R&D Project Selection

A two‐stage fuzzy approach for Industry 4.0 project portfolio selection within criteria and project interdependencies context

Contact Info

Product

Resources

About