A new multicriteria decision support tool based on fuzzy SWARA and TOPSIS

• Authors: Brahmi Hichem , Moalla Taicir Loukil
• Languages of publication: EN

Abstracts

EN

The problem of selecting 3PL (Third Party Logistics) suppliers is a major issue in the management of the supply chain and the improvement of the production management of a manufacturing company. A 3PL supplier can be defined as a company that provides contract logistics services to a manufacturer, supplier or main user of a product or service. It is called a third party because the logistics provider does not own the products but participates in the supply chain between the manufacturer and the user of a given product. In actual cases, several decision-makers intervene in the selection of 3PL suppliers and each one has his own points of view and wishes to take into account criteria which are not generally the same for all the decision-makers. Furthermore, the criteria have different weights. In this study, we propose a method to solve this problem. It consists of a combination of the fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) method with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The objective is to optimize the decision-making process and have another, more dynamic model and satisfy the needs of the decision-maker. Fuzzy SWARA is one of the new methods being used for ranking evaluation criteria based on decision makers’ expected degree of importance to determine the weights of evaluation criteria (Selçuk, 2019). This method can be used to facilitate estimation of decision makers’ preferences regarding the meaning of attributes in the weight determination process. TOPSIS is a multi-criteria method for identifying solutions from a finite set of alternatives (Behzadian et al., 2012). To the best of our knowledge, this combination has not been developed in the literature, especially in the third-party logistic problems. The proposed model will be implemented to solve a 3PL problem of a company selling steel products.

Keywords

EN

3PL suppliers; Fuzzy SWARA; Multicriteria decision support; TOPSIS

• Publisher: Uniwersytet Ekonomiczny w Katowicach
• Journal: Multiple Criteria Decision Making
• Year: 2021
• Volume: 16
• Pages: 5-22

Contributors

author

Brahmi Hichem

• University of Sfax, Faculty of Economics and Management Sciences of Sfax, Tunisia

author

Moalla Taicir Loukil

• University of Sfax, Faculty of Economics and Management Sciences of Sfax, Tunisia

References

• Batarlienė N., Jarašūnienė A. (2017), 3PL Service Improvement Opportunities in Transport Companies, 10th International Scientific Conference Transbaltica 2017: Transportation Science and Technology Procedia Engineering, 187, 67-76.
• Behzadian M., Otaghsara S.K., Yazdani M., Ignatius J. (2012), A State-of the-art Survey of TOPSIS Applications, Expert Systems with Applications, 39(17), 13051-13069.
• Bozdag C.E., Kahraman C., Ruan D. (2003), Fuzzy Group Decision Making for Selection among Computer Integrated Manufacturing Systems, Computers in Industry, 51(1), 13-29.
• Cabrerizo F.J., Herrera-Viedma E., Pedrycz W. (2013), A Method Based on PSO and Granular Computing of Linguistic Information to Solve Group Decision Making Problems Defined in Heterogeneous Contexts, European Journal of Operational Research, 230, 624-633.
• Chang D.Y. (1996), Applications of the Extent Analysis Method on Fuzzy AHP, European Journal of Operational Research, 95(3), 649-655.
• Chen N., Zeshui X. (2015), Hesitant Fuzzy ELECTRE II Approach: A New Way to Handle Multi-criteria Decision-making Problems, Information Sciences, 292, 175-197.
• Choy K.L., Lee W.B., Lo V. (2003), Design of a Case Based Intelligent Supplier Relationship Management System – The Integration of Supplier Rating System and Product Coding System, Expert Systems with Applications, 25, 87-100.
• Devendra Ch., Ravi Sh. (2014), A Goal Programming Model for Joint Decision Making of Inventory Lot-size, Supplier Selection and Carrier Selection, Computers & Industrial Engineering, 71, 1-9.
• Garcia Flores E., Bruch J., Wiktorsson M., Jackson, M. (2020), Decision-making Approaches in Process Innovations: An Explorative Case Study, Journal of Manufacturing Technology Management, 32(9), 1-25, doi:10.1108/jmtm-03-2019-0087.
• Ghodsypour S.H., O’Brien C. (2001), The Total Cost of Logistics in Supplier Selection, under Conditions of Multiple Sourcing, Multiple Criteria and Capacity Constraint, International Journal of Production Economics, 73, 15-27.
• Hosang J. (2017), Evaluation of Third-Party Logistics Providers Considering Social Sustainability, Asia Pacific School of Logistics, Inha University.
• Hyunjun L., Ayeon K., Aejin L., Boreum L., Hankwon L. (2021), Optimized H2 Fueling Station Arrangement Model Based on Total Cost of Ownership (TCO) of Fuel Cell Electric Vehicle (FCEV), International Journal of Hydrogen Energy, 46, 69, 34116-34127.
• Jain V., Benyoucef L. (2008), Managing Long Supply Chain Networks: Some Emerging Issues and Challenges, Journal of Manufacturing Technology Management, 29(4), 469-496, https://doi.org/10.1108/17410380810869923.
• Jain V., Wadhwa S., Deshmukh S.G. (2007), Supplier Selection Using Fuzzy Association Rules Mining Approach, International Journal of production Research, 41, 1323-131.
• Jellouli T., Benabdallah A. (2021), Mise en place de la méthode ABC pilotée par le temps (TDABC) et la création de valeur dans les services hospitaliers d’oncologie: De la revue de littérature à l’esquisse de modèle d’analyse, Alternatives Managériales et Economiques, 3(2), 162-179.
• Kahraman C., Ufuk C., Ziya U. (2003), Multi-criteria Supplier Selection Using Fuzzy AHP, Logistics Information Management, 16(6), 382-394.
• Karsak E.E., Dursun M. (2014), An Integrated Supplier Selection Methodology Incorporating QFD and DEA with Imprecise Data, Expert Systems with Applications, 41(16), 6957-4174.
• Keršulienė V., Zavadskas E.K., Z. Turskis (2010), Selection of Rational Dispute Resolution Method by Applying New Stepwise Weight Assessment Ratio Analysis (SWARA), Journal of Business Economics and Management, 11(2), 243-258.
• Kumar K.A. (2014), Revisiting the Supplier Selection Problem: An Integrated Approach for Group Decision Support, Expert Systems with Applications: An International Journal, 41, 2762-2771.
• Lambert D., Cooper M. (2000), Issues in Supply Chain Management, Industrial Marketing Management, 29(1), 65-83.
• Lin R.-H. (2009), An Integrated FANP–MOLP for Supplier Evaluation and Order Allocation, Applied Mathematical Modelling, 33(6), 2730-2736, doi: 10.1016/j.apm.2008.08.021.
• Mafakheri F., Breton M., Ghoniem A. (2011), Supplier Selection-order Allocation: A Two-stage Multiple Criteria Dynamic Programming Approach, International Journal of Production Economics, 132(1), 52-57, doi: 10.1016/j.ijpe.2011.03.005.
• Molla M.U., Giri B.C., Biswas P. (2021), Extended PROMETHEE Method with Pythagorean Fuzzy Sets for Medical Diagnosis Problems, Soft Computing, 25(6), 4503-4512, doi: 10.1007/s00500-020-05458-7.
• Nilay Y.G., Demirel N.C. (2012), Group Decision Making Process for Insurance Company Selection Problem with Extended VIKOR Method under Fuzzy Environment, Yıldız Technical University, Mechanical Faculty, Industrial Engineering Department, Beşiktaş, Istanbul, Turkey.
• Selçuk Perçin (2019), An Integrated Fuzzy SWARA and Fuzzy AD Approach for Outsourcing Provider Selection, Journal of Manufacturing Technology Management, https://doi.org/10.1108/ JMTM-08-2018-0247.
• Şengül U., Eren M., Shiraz S.E., Gezder V. (2015), Fuzzy TOPSIS Method for Ranking Renewable Energy Supply Systems in Turkey, Renewable Energy, 75, 617-625.
• Seyedkolaei A., Seno S.H. (2021), Multi-criteria Decision-making for Controller Placement in Software-defined Wide-area Networks, The Journal of Supercomputing, 62, https://doi.org/10.1007/s11227-021-03815-3.
• Tanonkou G.A., Benyoucef L., Xie X. (2007), A Scenario Analysis of a Location Problem with Uncertain Demand, International Journal of Computer Applications in Technology, 32(4), 290-297.
• Yan J., Chaudhry P.E., Chaudhry S.S. (2003), A Model of Decision Support System Based on Case-based Reasoning for Third-party Logistics Evaluation, Expert Systems, 20(4), 196-207.
• Yanhui Li, Hao G., Ying Z. (2018), An Integrated Location-inventory Problem in a Closed-loop Supply Chain with Third-party Logistics, International Journal of Production Research, 56(10), 3462-3481, https://doi.org/10.1080/00207543.2017.1338781.
• Zhang B., Li X., Lin B., Zhu Y. (2020), A CBR-based Decision-making Model for Supporting the Intelligent Energy-efficient Design of the Exterior Envelope of Public and Commercial Buildings, Energy and Buildings, 110625, doi: 10.1016/j.enbuild.2020.110625.
• Zhang C., Kumar A., Ré C.H. (2014), Materialization Optimizations for Feature Selection Workloads, ACM Transactions on Database Systems, 41, 1-32.
• Zouggari A., Benyoucef L. (2011), Une approche couplant logique floue et capitalisation des connaissances pour la résolution du problème de choix des fournisseurs, Mathématiques générales [math.GM], Université Paul Verlaine – Metz, https://hal.univ-lorraine.fr/tel-01749069.

Identifiers

ISSN

2084-1531