MCDM approach for selecting suitable solar tracking system

Chandrasekhar, Vishal; Marthuvanan, M.; Ramkumar, M.; Shriram, R.; Manickavasagam, V.M.; Ramnath, B. Vijaya

doi:10.1109/isco.2013.6481139

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…They indicated that it is necessary to calculate the weights of criteria to rank alternatives as a future study. Chandrasekhar et al used AHP method to rank solar tracking systems classified as active tracker, passive tracker, chronological tracker, and manual tracking in response, accuracy, repeatability, and reliability criteria. They determined chronological tracker as the best alternative with the weight of 0.4786.…”

Section: Use Of Mcdm Methods For Energy Policy and Decision Makingmentioning

confidence: 99%

Use of MCDM techniques for energy policy and decision-making problems: A review

2018

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Energy consumption increases all over the world as a result of industrialization in recent years. In this context, it has become important to meet increasing energy demand. It is significant to find alternative energy sources because of limited nonrenewable energy sources such as coal, petroleum, and natural gas. At this point, renewable energy sources have an important role to meet energy requirement. As a result, decision and policy making for energy is completely critical issue for countries. Various technical, economic, environmental, and social criteria are used to solve energy policy and decision-making problems such as evaluation of energy projects, selection among energy alternatives, power plant site selection, and determining energy policy. Multicriteria decision-making (MCDM) methods are used as effective tools to help decision makers while solving energy problems. There are a large number of studies including articles, conference papers, and book chapters, which examine energy problems by using MCDM methods in the literature. Therefore, analyzing these studies according to different features such as publication year, MCDM method, document type, statistical analyses, country, and published journal can be beneficial for leading researchers who study in energy decision-making field. In this study, published papers, which use traditional MCDM methods to handle energy problems, are examined systematically. By the way, it is aimed to lead to researchers regarding MCDM methods which are utilized in energy applications. It also conducted some statistical analyses to obtain trends between years and MCDM methods. Besides, recent developments in energy field are presented through this comprehensive literature review.

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Section: Use Of Mcdm Methods For Energy Policy and Decision Makingmentioning

confidence: 99%

Use of MCDM techniques for energy policy and decision-making problems: A review

2018

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“…Hosang Jung (2011) [9] evaluated that selection of manufacturing partners and integrated production-planning have become a critical issue so they utilized a fuzzy AHP to determine relative weights of manufacturing partners, while the GP is used to formulate the integrated production-planning problem. [10] used a multi criteria decision making (MCDM) model namely Analytic Hierarchy Process to determine the best possible solar tracking mechanism to achieve the optimum result for obtaining maximum solar energy from four main methods. Vijayaramnath et al (2010) [11] Proposed Analytic Hierarchy Process model for selecting supplier for leading glass product manufacturing industry.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of AHP and ANP Model for Lean Production System Justification

Venkataraman

Ramnath²,

Kannapan³

et al. 2014

AMM

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Industrial organizations are in great pressure to reduce costs, improve quality, cut down on lead times and improve flexibility. Companies are thus turning their attention to implement lean. This has created urgency to apply new tools and techniques to reduce various wastes. This paper deals with comparative analysis of analytic hierarchy process (AHP) and analytic network process (ANP) to select the best manufacturing process among traditional, lean and computer integrated manufacturing system. Six criteria such as quality, flexibility, productivity, innovation, morale and competitive advantage are considered for evaluation and also considering their sub criteria, the best manufacturing system is selected.

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Selection of solar tracking system using extended TOPSIS technique with interval type-2 pythagorean fuzzy numbers

et al. 2021

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The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is considered among the most frequently used techniques to deal with multi-criteria group decision-making (MCGDM) conflicts. In this article, we have presented an extended TOPSIS technique in the framework of interval type-2 trapezoidal Pythagorean fuzzy numbers (IT2TrPFN). We first projected a novel approach to evaluate the distance between them using ordered weighted averaging operator and $$(\alpha ,\beta )$$ ( α , β ) -cut. Subsequently, we widen the concept of TOPSIS method formed on the distance method with IT2TrPFNs and applied it on MCGDM dilemma by considering the attitudes and perspectives of the decision-makers. Lastly, an application of solar tracking system and numerous contrasts with the other existing techniques are presented to express the practicality and feasibility of our projected approach.

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MCDM approach for selecting suitable solar tracking system

Cited by 5 publications

References 19 publications

Use of MCDM techniques for energy policy and decision-making problems: A review

Use of MCDM techniques for energy policy and decision-making problems: A review

Comparative Analysis of AHP and ANP Model for Lean Production System Justification

Selection of solar tracking system using extended TOPSIS technique with interval type-2 pythagorean fuzzy numbers

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