A fuzzy ANP-based approach to R&amp;D project selection: A case study

Mohanty, R.P.; Agarwal, Renu; Choudhury, A.K.; Tiwari, Manoj Kumar

doi:10.1080/00207540500219031

Cited by 250 publications

(146 citation statements)

References 45 publications

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“…It's better to make project selection and assessment under fuzzy conditions. Fuzzy ANP is very useful in circumstances where there is a high degree of interdependence between various attributes of the project, for instance when the result of one criterion also affects the others (Mohanty et al, 2005). Taha and Daim (2013) mentioned that uncertainties and vagueness are inevitable in a decision making process.…”

Section: Literature Reviewmentioning

confidence: 99%

Selection of optimal renewable energy investment project via fuzzy ANP

Hamal¹,

Şenvar²,

Vayvay³

2018

Pressacademia

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Purpose -This study aims to determine the optimal renewable energy investment project providing a guideline to the investors in decision making process. Methodology -This study presents a comprehensive and solid mathematical approach considering the assessment of the ambiguities in the preferences of the decision maker for selection of the optimal renewable energy investment project via fuzzy analytic network process (FANP). FANP captures vagueness along with uncertainties in the evaluation. Findings -After FANP method had been implemented for the considered problem, Hydropower with 31% of importance is selected as optimum renewable energy investment project for the firm. Conclusion-This study provides a realistic assessment of energy resources and the consideration of the ambiguities presented in the preferences of the decision maker.

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Section: Literature Reviewmentioning

confidence: 99%

Selection of optimal renewable energy investment project via fuzzy ANP

Hamal¹,

Şenvar²,

Vayvay³

2018

Pressacademia

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“…The ANP can easily accommodate the interrelationships existing among the functional activities (Mohanty et al, 2005). In FANP, pair-wise comparison matrices are formed between each pairs of attributes at each level with the help of triangular fuzzy numbers.…”

Section: Fuzzy Anpmentioning

confidence: 99%

Integrated Fuzzy ANP, Fuzzy VIKOR and goal programming for sourcing in a supply chain: A case study from cable industry

Rezaei¹,

Naeeni²,

Motlagh³

2013

10.5267/j.dsl

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In today's competitive business environment, companies strive to increase their market shares. All companies clearly understand that they have to reach this goal by implementing cost effective methods and increase profits as much as possible. The cost of purchasing raw materials and component parts are significant portion of products in most manufacturing firms. Supplier selection and evaluation have been widely recognized to be one of the most substantial issues on material purchasing. In order to choose reliable suppliers it is necessary to have a trade-off between some tangible and intangible factors where some of them are in serious conflict. In this paper, an integrated technique of analytical network process improved by VIKOR and fuzzy sets theory and multi-objective mixed integer nonlinear programming is proposed to determine the appropriate suppliers. The proposed model of this paper also determines the order quantity allocated to each supplier in the case of multiple sourcing, multiple products and multi-period time horizon for an Iranian cable company.

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“…Barclay and Dann (2000), Balachandra and Friar(1997), Griffin(1997) 예상 개발 위험 (expected development risk : EDR) Mohanty et al(2005), Astebro(2004) R&D 역량 (R&D competency)…”

Section: 서 론 기술개발의 성공 가능성을 예측하는 것은 기술예측(Technologic-mentioning

confidence: 99%

An Analytic Network Process(ANP) Approach to Forecasting of Technology Development Success : The Case of MRAM Technology

Jeon¹,

Cho²,

Lee³

2012

IE interfaces

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Forecasting probability or likelihood of technology development success has been a crucial factor for critical decisions in technology management such as R&D project selection and go or no-go decision of new product development (NPD) projects. This paper proposes an analytic network process (ANP) approach to forecasting of technology development success. Reviewing literature on factors affecting technology development success has constructed the ANP model composed of four criteria clusters : R&D characteristics, R&D competency, technological characteristics, and technological environment. An alternative cluster comprised of two elements, success and failure is also included in the model. The working of the proposed approach is provided with the help of a case study example of MRAM (magnetic random access memory) technology. 1)

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A fuzzy ANP-based approach to R&D project selection: A case study

Cited by 250 publications

References 45 publications

Selection of optimal renewable energy investment project via fuzzy ANP

Selection of optimal renewable energy investment project via fuzzy ANP

Integrated Fuzzy ANP, Fuzzy VIKOR and goal programming for sourcing in a supply chain: A case study from cable industry

An Analytic Network Process(ANP) Approach to Forecasting of Technology Development Success : The Case of MRAM Technology

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