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Growing Science » Authors » Esra Aytaç Adalı

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Naser Azad(82)
Mohammad Reza Iravani(64)
Zeplin Jiwa Husada Tarigan(63)
Endri Endri(45)
Muhammad Alshurideh(42)
Hotlan Siagian(39)
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Sort articles by: Volume | Date | Most Rates | Most Views | Reviews | Alphabet
1.

Integration of DEMATEL, ANP and DEA methods for third party logistics providers’ selection Pages 325-340 Right click to download the paper Download PDF

Authors: Esra Aytaç Adalı, Ayşegül Tuş Işık

DOI: 10.5267/j.msl.2016.3.004

Keywords: Analytic Network Process (ANP), Data Envelopment Analysis (DEA), Decision Making Trial and Evaluation Laboratory (DEMATEL), Third Party Logistics (TPL)

Abstract:
In a competitive environment many companies usually outsource their logistics functions to the Third Party Logistics (TPL) providers to focus on their core businesses. However, the selection of proper TPL provider is not an easy task because of conflicting quantitative and qualitative criteria. This study presents an integrated model based on three well-known methods Decision Making Trial and Evaluation Laboratory (DEMATEL), Analytical Network Process (ANP) and Data Envelopment Analysis (DEA) for the evaluation and selection of TPL providers. DEMATEL computes the effects between selection criteria while ANP derives the weights of each criterion related with TPL providers’ selection problem. Finally DEA presents a mathematical model for ranking TPL providers alternatives with respect to various criteria. The application of integrated model is demonstrated with a case study. The novelty of this study comes from the fact that there is no research in the literature integrating DEMATEL, ANP and DEA for the TPL selection problems.
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Journal: MSL | Year: 2016 | Volume: 6 | Issue: 5 | Views: 3275 | Reviews: 0

 
2.

A comparative study for the agricultural tractor selection problem Pages 569-580 Right click to download the paper Download PDF

Authors: Ayşegül Tuş Işık, Esra Aytaç Adalı

DOI: 10.5267/j.dsl.2016.3.002

Keywords: COPRAS, EVAMIX, Borda, Copeland

Abstract:
Agricultural tractor selection is vital for farms, farmers or other agricultural companies in terms
of success and competitiveness in the global market. This selection may be assumed as a
MCDM (Multi Criteria Decision Making) problem involving qualitative and quantitative
factors that must be simultaneously integrated into the selection process. At the same time there
are many agricultural tractor alternatives in the market when purchasing an agricultural tractor.
This paper deals with the agricultural tractor selection problem using TOPSIS method. This
problem is also solved with two other MCDM methods; COPRAS (COmplex PRoportional
ASsessment) and EVAMIX (EVAluation of MIXed Data) to rank the tractors alternatives.
Lastly Borda and Copeland methods are used to aggregate all three ranking results.
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Journal: DSL | Year: 2016 | Volume: 5 | Issue: 4 | Views: 2727 | Reviews: 0

 
3.

An alternative approach based on Fuzzy PROMETHEE method for the supplier selection problem Pages 183-194 Right click to download the paper Download PDF

Authors: Esra Aytaç Adalı, Ayşegül Tuş Işık, Kundakcı Kundakcı

DOI: 10.5267/j.uscm.2016.2.002

Keywords: Fuzzy PROMETHEE, Linguistic variables, Multi Criteria Decision Making (MCDM), Preference functions

Abstract:
In this paper, an alternative version of the fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) method is proposed. Differently from other studies, preference functions used in PROMETHEE method are handled in terms of fuzzy distances between alternatives with respect to each criterion. In order to indicate the applicability of this method, the method is applied for a supplier selection problem in the literature. Ranking results are similar obtained by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and fuzzy ELECTRE (ELimination Et Choix Traduisant la REalité) methods. The implementation of the proposed method indicates that the amount of computations is decreased and decision makers can easily reach to desirable solution.
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Journal: USCM | Year: 2016 | Volume: 4 | Issue: 3 | Views: 4007 | Reviews: 0

 

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