Extension of the TOPSIS method for decision-making problems with fuzzy data

Jahanshahloo, G. R.; Lotfı, Farhad Hosseinzadeh; Izadikhah, Mohammad

doi:10.1016/j.amc.2006.02.057

Cited by 474 publications

(237 citation statements)

References 5 publications

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“…This normalization is the norm L 1 version of the normalization method proposed in (Jahanshahloo et al, 2006)…”

Section: Entropy Methods With Interval Datamentioning

confidence: 99%

A novel method to extend SAW for decision-making problems with interval data

Alireza¹,

Izadikhah²

2014

10.5267/j.dsl

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Decision making problem is the process of finding the best option out of all feasible alternatives. There are some methods for solving Multiple Criteria Decision-Making problems and Simple Additive Weighting (SAW) is one of the most popular ones. In this paper, among multi-criteria models in making complex decisions and multiple attribute models for the most preferable choice, SAW technique is extended using interval numbers. For this purpose, we first propose a method for extending Entropy method for dealing with interval data, and then the extended SAW method with interval data is proposed by using the interval weights derived by the proposed interval Entropy method. The extended SAW method is an algorithm to determine the most preferable choice out of all possible choices, when the input data are stated in interval.

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“…This normalization is the norm L 1 version of the normalization method proposed in (Jahanshahloo et al, 2006)…”

Section: Entropy Methods With Interval Datamentioning

confidence: 99%

A novel method to extend SAW for decision-making problems with interval data

Alireza¹,

Izadikhah²

2014

10.5267/j.dsl

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“…Allocating weight for indicators is a key procedure of the TOPSIS method, and the entropy weight method provides the objective weight. The procedures of TOPSIS can be presented as follows [41][42][43][44][45].…”

Section: Topsis Methodsmentioning

confidence: 99%

Multi-Layered Capital Subsidy Policy for the PV Industry in China Considering Regional Differences

Chi

Zhang

et al. 2016

Sustainability

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Abstract:As a country with huge energy consumption, China has been paying more and more attention to green growth in recent years. Several subsidy policies have been conducted to boost the photovoltaic (PV) industry so far. However, as a matter of fact, there are 31 provinces and municipalities (PM) in mainland China, and the economic condition, environmental resources and energy structure of each PM are all significantly different, which leads to a discrepancy of PV efficiency among regions. This paper proposes that the subsidies for the PV industry should be considered mainly from three aspects: the PM's economic condition, energy efficiency and environmental responsibility. We built 19 evaluation indicators involving economic, environmental and energy factors, allocated weight to each indicator using the entropy weight method and sorted the 31 evaluation objects by TOPSIS (Technique for Order of Preference by Similarity to the Ideal Solution) method. Additionally, through an empirical study, we obtained the subsidy proportion for each PM. The result could make much of a contribution to the green growth of different regions and to the whole country.

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“…During the years, many authors such as Chen [40] ; Negi et al [44] , Chen et al [41] ; Chen and Hwang [45] ; Chen and Tzeng [46] ; Jahanshahloo, Hosseinzadeh Lotfi, and Izadikhah [47] ; Liang [48] ; Wang and Elhag [49] ; Wang and Lee [50] ; Wang, Luo, and Hua [51] ; Yeh, Deng, and Chang [52] ; and Yeh and Deng [53] , and Zare Mehrjerdi [54,55] have contributed new materials on the development, extensions and applications of TOPSIS since its early development in 1981. Its general extension for group decision making problems under fuzzy environment was published by Chen [40] .…”

Section: Multiple Criteria Decision Makingmentioning

confidence: 99%

Group decision making process for RFID-based system selection using fuzzy TOPSIS approach

Mehrjerdi

2013

AIR

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The purpose of this article is twofold: first to introduce a multi attribute decision making model for radio frequency identification system consisting of four main criteria and five alternatives, and second to develop and solve the proposed fuzzy TOPSIS problem. Author presented an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ideal solution points for solving problems with a group of multi decision makers. The fuzzy sets concepts are used to evaluate the performance of alternatives and the importance of criteria. The TOPSIS model used in this article is able to grasp the ambiguity exists in the utilized information and the fuzziness appears in the human judgments and preferences. TOPSIS technique can easily produce satisfactory results, and hence stimulates creativity and the invention for developing new methods and alternative approaches. This article is a very useful source of information both for radio frequency identification and multi attribute decision making using fuzzy TOPSIS methodology.

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Extension of the TOPSIS method for decision-making problems with fuzzy data

Cited by 474 publications

References 5 publications

A novel method to extend SAW for decision-making problems with interval data

A novel method to extend SAW for decision-making problems with interval data

Multi-Layered Capital Subsidy Policy for the PV Industry in China Considering Regional Differences

Group decision making process for RFID-based system selection using fuzzy TOPSIS approach

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