Comparison of weights in TOPSIS models

Olson, David L.

doi:10.1016/j.mcm.2004.10.003

Cited by 628 publications

(305 citation statements)

References 22 publications

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“…Either actual values of the requirements against the various barrier alternatives or the use of linguistic variables correlated with fuzzy numbers to identify the ratings and weights could be the input in the decision making (Shahanaghi et al, 1999). It may be noted that the weight of a criterion is an important aspect and some authors suggest using the Analytical Hierarchical Process (AHP) or other techniques to obtain the weights, as in the study of Shih et al (2001; and Olson et al (2004). However, in the present study, the topic of weight elicitation is not considered, as it is assumed that the weights of attributes or criteria are judiciously decided by the expert decision makers, D1, D2, and D3.…”

Section: Topsis Methodologymentioning

confidence: 99%

Fuzzy TOPSIS Approach in Selection of Optimal Noise Barrier for Traffic Noise Abatement

Garg¹,

Vishesh²,

Maji³

2015

Archives of Acoustics

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The paper presents a retrospective study for selection of noise barrier for road traffic noise abatement. The work proposes the application of Fuzzy TOPSIS (Technique for order preference by similarity to an ideal solution) approach is selection of optimal road traffic noise barrier. The present work utilizes the fuzzy TOPSIS model proposed by Mahdavi et al. (2008) in determination of ranking order of various types of noise barriers with respect to the various criteria considered. It is suggested that application of this approach can be very helpful in selection and application of optimal noise barrier for road traffic noise abatement.

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Section: Topsis Methodologymentioning

confidence: 99%

Fuzzy TOPSIS Approach in Selection of Optimal Noise Barrier for Traffic Noise Abatement

Garg¹,

Vishesh²,

Maji³

2015

Archives of Acoustics

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“…There have been lots of studies in the literature using TOPSIS for the solution of MCDM problems. (Chen, 2000;Chu, 2002;Chu and Lin, 2002;Lai et al, 1994;Olson 2004;Wang et al, 2005;Yang et Step 1: Establish a decision matrix for the ranking. The structure of the matrix can be expressed as follows: where A j denotes the alternatives j, j = 1, 2,…, J; F i represents the ith attribute or criterion, i = 1, 2,…, n, related to the ith alternative; and f ij is a crisp value indicating the performance rating of each alternative A i with respect to each criterion F j .…”

Section: S-topsis -S-topsismentioning

confidence: 99%

Planning of environmentally sound forest road route using GIS & S-MCDM

Çalışkan

2017

Šumar. list (Online)

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SummaryForest roads are basic precondition for the sustainable management of forest resources. These roads entail a complex engineering effort because they can cause substantial environmental damage to forests and include a highcost construction. Therefore, the design of forest road routes should have taken into account in terms of environmental impacts. In order to do this, the Geographical Information System (GIS) with Spatial Multi Criteria Decision Making (S-MCDM) techniques is a useful tool for creating a model. One such S-MCDM is the Spatialintegrated Technique for Order Preference by Similarity to Ideal Solution (S-TOPSIS). In this study, S-TOPSIS was applied to integrate environmental impacts into the design of a forest road route. Using the current forest road route (CFOR) and the GIS-based S-TOPSIS method, an environmentally sound forest road route (ESFOR) was determined according to environmental criteria. Five environmental criteria (avalanche, river, soil, geology and slope) were used for analysis to compare with. The results obtained from the analyses, are compared to the current forest road route. The CFOR 15.385 km in length, while the ESFOR found by S-TOPSIS was 14.385 km. If the differences in length between two roads multiplied by the width of the road (1km X 5m), the result would be 0.5 ha. The results showed that this methodology can provide environmentally sound road network also help to design quickly and less costly. These results suggest that spatial multi criteria decision making method can be more accurate in terms of environmentally sensitive forest road designing in mountainous area.

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“…TOPSIS yöntemiyle elde edilen en iyi çözüm; ideal çözüme en yakın, aynı zamanda antiideal çözüme de en uzak olan alternatiftir. TOPSIS, finans yatırımlarından üretim sistemlerine kadar çok kriterli karar vermenin gerektiği gerçek dünya problemleri ile akademik araştırmalarda sıkça kullanılmaktadır [9]. TOPSIS'in uygulandığı problemler arasında aday değerlendirme [17], konteyner limanlarının yönetimi [18], eğitim stratejisi belirlenmesi [19], silah seçimi [20], uzman personel seçimi [21] imalat işçisi seçimi [22], ürün tasarımı [23], imalat yöntemi seçimi [24], bina enerji performansı İdeal çözüme göreceli yakınlık değerlerinin hesaplanması.…”

Section: Topsis Yöntemi̇ (Topsis Technique)unclassified

“…Satranç tahtası uzaklığı olarak da isimlendirilir. TOPSIS içinde beyzbol ligi kazananlarının tahmini için ele alınmıştır [9]. …”

Section: Topsis Yöntemi̇ (Topsis Technique)unclassified

“…TOPSIS yöntemi algoritmasında diğer normalizasyon teknikleri kullanıldığında ortaya çıkan farklılıklar incelenmesine rağmen [8] pozitif ve negatif ideal çözüme uzaklık hesaplanırken Öklid uzaklığından farklı diğer yöntemlerin nasıl bir etki yaratacağını inceleyen çok az sayıda çalışma vardır. Bu çalışmalarda Öklid uzaklığından farklı olarak doğrusal uzaklık [9], küresel uzaklık [10], Hamming uzaklığı [10], Chebyshev uzaklığı [11], Dice uzaklığı [12], Jaccard uzaklığı [12] ve kosinüs uzaklığı [13] dikkate alınmıştır. Bu uzaklık ölçütlerinin ele alınması ile elde edilen sonuç ve sıralamaları inceleyen kısımlar oldukça kısıtlı kalmıştır.…”

Section: Gi̇ri̇ş (Introduction)unclassified

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