Location selection for logistics center with fuzzy SWARA and CoCoSo methods

Ulutaş, Alptekin; Karakus, Can; Topal, Ayşe

doi:10.3233/jifs-191400

Cited by 115 publications

(56 citation statements)

References 30 publications

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“…Some examples of the application of the fuzzy SWARA method with an inadequate scale were given in studies [37][38][39][40]. It should be noted that the future application of the fuzzy SWARA method should be replaced by the improved fuzzy SWARA (IMF SWARA) method or the application of another scale in fuzzy SWARA that eliminates these previously observed shortcomings.…”

Section: Improved Fuzzy Swara Methods (Imf Swara)mentioning

confidence: 99%

Ranking Road Sections Based on MCDM Model: New Improved Fuzzy SWARA (IMF SWARA)

Vrtagic

Softić

Subotić

et al. 2021

Axioms

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Traffic management is a significantly difficult and demanding task. It is necessary to know the main parameters of road networks in order to adequately meet traffic management requirements. Through this paper, an integrated fuzzy model for ranking road sections based on four inputs and four outputs was developed. The goal was to determine the safety degree of the observed road sections by the methodology developed. The greatest contribution of the paper is reflected in the development of the improved fuzzy step-wise weight assessment ratio analysis (IMF SWARA) method and integration with the fuzzy measurement alternatives and ranking according to the compromise solution (fuzzy MARCOS) method. First, the data envelopment analysis (DEA) model was applied, showing that three road sections have a high traffic risk. After that, IMF SWARA was applied to determine the values of the weight coefficients of the criteria, and the fuzzy MARCOS method was used for the final ranking of the sections. The obtained results were verified through a three-phase sensitivity analysis with an emphasis on forming 40 new scenarios in which input values were simulated. The stability of the model was proven in all phases of sensitivity analysis.

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Section: Improved Fuzzy Swara Methods (Imf Swara)mentioning

confidence: 99%

Ranking Road Sections Based on MCDM Model: New Improved Fuzzy SWARA (IMF SWARA)

Vrtagic

Softić

Subotić

et al. 2021

Axioms

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“…The method was initially introduced in 2019 and was developed for uncertain versions including Pythagorean Fuzzy (Taghavifard et al, 2018;Peng et al, 2020), grey/interval , interval rough (Erceg et al, 2019), fuzzy CoCoSo (Ecer and Pamucar, 2020) and hesitant fuzzy . This method has been recently used for many scientific investigations including the assessment of sustainable development goals (Stanujkic et al, 2020), facility location problems (Ulutas et al, 2020), performance assessment problems Kharwar et al, 2020), stock management (Erceg et al, 2019) and supplier selection (Zolfani et al, 2019;Ecer and Pamucar, 2020). This wide range of applications demonstrates the fact that this method is a popular and reliable algorithm for any multi-criteria decision-making problem.…”

Section: Combined Compromise Solution Methodsmentioning

confidence: 99%

Classification of inter-organizational knowledge mechanisms and their effects on networking capability: a multi-layer decision making approach

Mokhtarzadeh

Mahdiraji

Jafarpanah

et al. 2021

JKM

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Purpose The role of inter-organizational knowledge mechanisms (IOKMs) in learning networks is increasing so that the competition of business networks in providing innovations is highly dependent on the effective selection and application of these mechanisms. This study aims to argue that recognizing the classification of IOKMs and understanding their impact on networking capability (NC) makes the selection of mechanisms more effective. Design/methodology/approach With a systematic review of literature, a comprehensive list of IOKMs, their main characteristics and NCs have been extracted. The authors have used a focus group for data gathering and a hybrid multi-layer decision-making approach for data analysis. Finally, the impact of IOKMs on NC was determined. Findings By implementing a multi-layer decision-making approach, four categories of IOKMs including person-to-person, co-creation, team-oriented and informational are illustrated and their effects of NC are determined. Therefore, the findings of this research provide latecomer firms (LCFs) managers with a clear framework for selecting IOKMs. Originality/value The literature review shows that the number of knowledge mechanisms, especially their inter-organizational types, is increasing. It has made it difficult for LCFs managers to select effective and efficient mechanisms. Most of these mechanisms are listed, and few studies have classified them. Besides, research shows that fewer studies have investigated how IOKMs relate to NC. Furthermore, most studies on IOKMs have been conducted in the context of leading firms and LCFs have been neglected.

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“…Peng et al [75] presented a Pythagorean fuzzy CRITIC-CoCoSo approach to assess communication products of 5th generation enterprises. Ulutaş et al [76] proposed a GIS-based fuzzy SWARA-CoCoSo approach to rank suitable locations for a logistics center. Yazdani et al [77] presented a rough FUCOM-CoCoSo approach to evaluate geographical areas for a logistics center.…”

Section: Applications and Extensions Of The Cocoso Methodsmentioning

confidence: 99%

Picture Fuzzy Decision-Making Approach for Sustainable Last-Mile Delivery

et al. 2020

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In light of the increasing importance of last-mile delivery (LMD) and the associated high costs, air pollution, and logistical challenges, research on sustainable LMD is highly trending and dynamic. The selection of sustainable LMD mode is an emerging problem for decision-makers in the logistics industry. The key question is how to determine the best LMD mode from a set of alternatives under numerous criteria with ambiguous, vague, and uncertain sustainability-related information. This paper aims to provide an advanced decision-making approach for sustainable LMD. Firstly, 20 sustainable LMD mode evaluation criteria are identified. Secondly, picture fuzzy sets (PFSs) are exploited to help decision-makers to more naturally express their preferences by voting. Thirdly, a hybrid picture fuzzy criteria weighting method based on the Direct rating and R-norm entropy is developed to compute the importance of evaluation criteria. Fourthly, a novel picture fuzzy Combined Compromise Solution method is formulated to rank alternative LMD modes. Fifthly, the presented picture fuzzy approach for sustainable LMD is implemented in the real-life decision-making context. The results show that "e-cargo bike" is the best alternative in the Pardubice context. The comparative analysis with three state-of-the-art PFS-based MCDM methods approved the high reliability of the provided approach. The sensitivity analyses of the trade-off parameter and balancing factor confirmed the high robustness of the presented approach. The introduced approach can help decision-makers in the logistics industry to elucidate sustainable LMD mode. It can solve not only the highlighted problem but also other MCDM problems under the picture fuzzy environment.

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Location selection for logistics center with fuzzy SWARA and CoCoSo methods

Cited by 115 publications

References 30 publications

Ranking Road Sections Based on MCDM Model: New Improved Fuzzy SWARA (IMF SWARA)

Ranking Road Sections Based on MCDM Model: New Improved Fuzzy SWARA (IMF SWARA)

Classification of inter-organizational knowledge mechanisms and their effects on networking capability: a multi-layer decision making approach

Picture Fuzzy Decision-Making Approach for Sustainable Last-Mile Delivery

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