scholarly journals A NEW INTEGRATED GREY MCDM MODEL: CASE OF WAREHOUSE LOCATION SELECTION

2021 ◽  
Vol 19 (3) ◽  
pp. 515
Author(s):  
Alptekin Ulutaş ◽  
Figen Balo ◽  
Lutfu Sua ◽  
Ezgi Demir ◽  
Ayşe Topal ◽  
...  
Keyword(s):  
Supply Chain ◽  
Selection Process ◽  
Selection Index ◽  
Grey Theory ◽  
Model Case ◽  
Location Selection ◽  
Warehouse Location ◽  
Criteria Weights ◽  
Logistics Process ◽  
First Time

Warehouses link suppliers and customers throughout the entire supply chain. The location of the warehouse has a significant impact on the logistics process. Even though all other warehouse activities are successful, if the product dispatched from the warehouse fails to meet the customer needs in time, the company may face with the risk of losing customers. This affects the performance of the whole supply chain therefore the choice of warehouse location is an important decision problem. This problem is a multi-criteria decision-making (MCDM) problem since it involves many criteria and alternatives in the selection process. This study proposes an integrated grey MCDM model including grey preference selection index (GPSI) and grey proximity indexed value (GPIV) to determine the most appropriate warehouse location for a supermarket. This study aims to make three contributions to the literature. PSI and PIV methods combined with grey theory will be introduced for the first time in the literature. In addition, GPSI and GPIV methods will be combined and used to select the best warehouse location. In this study, the performances of five warehouse location alternatives were assessed with twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results were compared with other grey MCDM methods, and it was found that GPIV method is reliable. It has been determined from the sensitivity analysis that the change in criteria weights causes a change in the ranking of the locations therefore GPIV method was found to be sensitive to the change in criteria weights.

scholarly journals A Hybrid MCDM Approach in Third-Party Logistics (3PL) Provider Selection

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2729
Author(s):  
Stefan Jovčić ◽  
Petr Průša
Keyword(s):  
Selection Process ◽  
High Reliability ◽  
Third Party ◽  
Sensitivity Analyses ◽  
Third Party Logistics ◽  
Logistics Industry ◽  
Criteria Weights ◽  
Criteria Importance ◽  
First Time

Third-party logistics (3PL) is becoming more and more popular because of globalization, e-commerce development, and increasing customer demand. More and more companies are trying to move away from their own account transportation to third-party accounts. One reason for using 3PLs is that the company can focus more on its core activities, while the 3PL service provider can provide distribution activities in a more professional way, save costs and time, and increase the level of customer satisfaction. An emerging issue for companies in the logistics industry is how they can decide on the 3PL evaluation and selection process for outsourcing activities. For the first time, the entropy and the criteria importance through intercriteria correlation (CRITIC) methods were coupled in order to obtain hybrid criteria weights that are of huge importance to decide on the 3PL provider evaluation and selection process. The obtained criteria weights were further utilized within the additive ratio assessment (ARAS) method to rank the alternatives from the best to the worst. The introduced hybrid–ARAS approach can be highly beneficial, since combining two methods gives more robust solutions on one hand, while on the other hand eliminating subjectivity. Comparative and sensitivity analyses showed the high reliability of the proposed hybrid–ARAS method. A hypothetical case study is presented to illustrate the potentials and applicability of the hybrid–ARAS method. The results showed that 3PL-2 was the best possible solution for our case.

scholarly journals Supplier Selection by Using a Fuzzy Integrated Model for a Textile Company

2019 ◽  
Vol 30 (5) ◽  
pp. 579-590 ◽  
Author(s):  
Alptekin ULUTAŞ
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Model ◽  
Selection Problem ◽  
Grey Theory ◽  
Chain Management ◽  
Fuzzy Mcdm ◽  
Supplier Selection Problem

Supply chain management determining the competitive position of corporations in a rival and fast-changing environment is one of the favourite topics in engineering economics. Since the performance of suppliers affects the performance of the whole supply chain, the selection of a supplier is a significant problem in supply chain management. When solving a supplier selection problem, there are many criteria needed to be considered. Therefore, the supplier selection problem is a multi-criteria decision making (MCDM) problem. In the supplier selection process, most of the time, expert data is involved, and the judgement of experts includes ambiguous, imprecise and uncertain data. Thus, there are many methods to solve supplier selection issues by utilising fuzzy set theory, grey theory and rough theory to handle vagueness of a problem. This study also proposes a fuzzy model to solve this problem. In this study, an integrated fuzzy MCDM model including the Fuzzy Analytic Hierarchy Process (FAHP) and the Fuzzy Operational Competitiveness RAting (Fuzzy OCRA) will be proposed to solve supplier selection problem for a Turkish textile company. The FAHP is utilised to determine the weights of considered eight criteria and the fuzzy OCRA is used to rank five fabric suppliers concerning their performances on eight measures. This study is original and it contributes to the literature in two ways: first, this study proposes a fuzzy extension of the OCRA method and second, this study offers a new integrated fuzzy MCDM model consisting of the FAHP and the Fuzzy OCRA. By using a real case study of supplier selection problem, it is attempted to indicate the applicability of the new integrated fuzzy MCDM model for actual circumstances.

scholarly journals A New Integrated Multi-Criteria Decision-Making Model for Resilient Supplier Selection

2022 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Wan Yee Leong ◽  
Kuan Yew Wong ◽  
Wai Peng Wong
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Financial Stability ◽  
Supplier Selection ◽  
Selection Process ◽  
Research Direction ◽  
Multi Criteria Decision Making ◽  
Criteria Weights ◽  
Managerial Implications ◽  
Criteria Importance

Unexpected worldwide disruptions brought various challenges to supply chain management thus manipulating the research direction towards resilience. Since the supplier is one of the important supply chain elements, the challenges can be overcome through resilient supplier selection. Supplier selection is a multi-criteria decision-making problem where several criteria are involved. In this study, GRA-BWM-TOPSIS was proposed to evaluate resilient suppliers. Seven resilience criteria which were Quality, Lead Time, Cost, Flexibility, Visibility, Responsiveness and Financial Stability have been proposed and five experts were selected to provide judgments for the selection process. By using the proposed method, the criteria importance levels were obtained using GRA and the criteria weights were computed using BWM, together with a consistency test. TOPSIS was applied to evaluate the suppliers’ performances. Through a case study in a food manufacturing company, 10 suppliers were evaluated and ranked. A validation process was carried out and the managerial implications were provided to ensure the effectiveness of the proposed model. GRA-BWM-TOPSIS is suitable for resilient supplier selection when there are uncertainties and incomplete data.

scholarly journals Comparative Analysis of Hybrid Fuzzy MCGDM Methodologies for Optimal Robot Selection Process

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 839
Author(s):  
Tabasam Rashid ◽  
Asif Ali ◽  
Juan Guirao ◽  
Adrián Valverde
Keyword(s):  
Selection Process ◽  
Industrial Robot ◽  
Vital Role ◽  
Decision Makers ◽  
Fuzzy Information ◽  
Criteria Weights ◽  
Topsis Technique ◽  
Fuzzy Weights ◽  
Robot Selection ◽  
Interval Valued

The generalized interval-valued trapezoidal fuzzy best-worst method (GITrF-BWM) provides more reliable and more consistent criteria weights for multiple criteria group decision making (MCGDM) problems. In this study, GITrF-BWM is integrated with the extended TOPSIS (technique for order preference by similarity to the ideal solution) and extended VIKOR (visekriterijumska optimizacija i kompromisno resenje) methods for the selection of the optimal industrial robot using fuzzy information. For a criteria-based selection process, assigning weights play a vital role and significantly affect the decision. Assigning weights based on direct opinions of decision makers can be biased, so weight deriving models, such as GITrF-BWM, overcome this discrepancy. In previous studies, generalized interval-valued trapezoidal fuzzy weights were not derived by using any MCGDM method for the robot selection process. For this study, both subjective and objective criteria are considered. The preferences of decision makers are provided with the help of linguistic terms that are then converted into fuzzy information. The stability and reliability of the methods were tested by performing sensitivity analysis, which showed that the ranking results of both the methodologies are not symmetrical, and the integration of GITrF-BWM with the extended TOPSIS method provides stable and reliable results as compared to the integration of GITrF-BWM with the extended VIKOR method. Hence, the proposed methodology provides robust optimal industrial robot selection.

scholarly journals Prioritization of public services for digitalization using fuzzy Z-AHP and fuzzy Z-WASPAS

2021 ◽  
Author(s):  
Duygu Sergi ◽  
Irem Ucal Sari
Keyword(s):  
Health Care ◽  
Public Transportation ◽  
Health Care Services ◽  
Public Services ◽  
Fast Response ◽  
Care Services ◽  
Citizen Complaints ◽  
Criteria Weights ◽  
Available Information ◽  
First Time

AbstractIn this paper, public services are analyzed for implementations of Industry 4.0 tools to satisfy citizen expectations. To be able to prioritize public services for digitalization, fuzzy Z-AHP and fuzzy Z-WASPAS are used in the analysis. The decision criteria are determined as reduced cost, fast response, ease of accessibility, reduced service times, increase in the available information and increased quality. After obtaining criteria weights using fuzzy Z-AHP, health care services, waste disposal department, public transportation, information services, social care services, and citizen complaints resolution centers are compared using fuzzy Z-WASPAS that is proposed for the first time in this paper. Results show that health care services have dominant importance for the digitalization among public services.

scholarly journals A Dispatching-Fuzzy AHP-TOPSIS Model for Scheduling Flexible Job-Shop Systems in Industry 4.0 Context

2021 ◽  
Vol 11 (11) ◽  
pp. 5107
Author(s):  
Miguel Ortíz-Barrios ◽  
Antonella Petrillo ◽  
Fabio De Felice ◽  
Natalia Jaramillo-Rueda ◽  
Genett Jiménez-Delgado ◽  
...  
Keyword(s):  
Job Shop ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Flexible Job Shop ◽  
Criteria Weights ◽  
Dispatching Algorithm ◽  
Scheduling Method ◽  
Hard Problems ◽  
Fourth Step

Scheduling flexible job-shop systems (FJSS) has become a major challenge for different smart factories due to the high complexity involved in NP-hard problems and the constant need to satisfy customers in real time. A key aspect to be addressed in this particular aim is the adoption of a multi-criteria approach incorporating the current dynamics of smart FJSS. Thus, this paper proposes an integrated and enhanced method of a dispatching algorithm based on fuzzy AHP (FAHP) and TOPSIS. Initially, the two first steps of the dispatching algorithm (identification of eligible operations and machine selection) were implemented. The FAHP and TOPSIS methods were then integrated to underpin the multi-criteria operation selection process. In particular, FAHP was used to calculate the criteria weights under uncertainty, and TOPSIS was later applied to rank the eligible operations. As the fourth step of dispatching the algorithm, the operation with the highest priority was scheduled together with its initial and final time. A case study from the smart apparel industry was employed to validate the effectiveness of the proposed approach. The results evidenced that our approach outperformed the current company’s scheduling method by a median lateness of 3.86 days while prioritizing high-throughput products for earlier delivery.

Optimization of E-Commerce Logistics Process of Automobile Manufacturing Enterprise Based on ARIS

2012 ◽  
Vol 542-543 ◽  
pp. 457-461 ◽  
Author(s):  
Shou Wen Ji ◽  
Cheng Chen ◽  
Wen Ling Wu
Keyword(s):  
Supply Chain ◽  
Production Process ◽  
Manufacturing Enterprise ◽  
Automobile Manufacturing ◽  
Purchase Process ◽  
Logistics Process

In the document, ARIS method is used to establish an E-Commerce logistics process module of automobile manufacturing enterprise, including overall process, production process, logistics process and purchase process. The document analyzes the optimization and reforming of distribution business of automobile manufacturing enterprise, which is in intensive supply chain mode.

Supply Chain Management System Design in Vendor Selection Process

2021 ◽  
Author(s):  
Oryza Putri Suriana ◽  
Alfan Reynaldo ◽  
Muhammad Dwi Ferdian Suwardi ◽  
Indra Kusumadi Hartono
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
System Design ◽  
Management System ◽  
Selection Process ◽  
Vendor Selection ◽  
Chain Management ◽  
Supply Chain Management System

Determining criteria interaction and criteria priorities in the freight village location selection process: the experts' perspective in Turkey

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mehmet Pekkaya ◽  
Nuh Keleş
Keyword(s):  
Environmental Sustainability ◽  
Selection Process ◽  
Transportation Cost ◽  
Social Dimensions ◽  
Labor Costs ◽  
Content Type ◽  
Location Selection ◽  
Interaction Diagram ◽  
Market Opportunities ◽  
Trade Potential

PurposeConsidering the contribution of freight villages (FVs) to the economy and sector, transportation cost advantage, environmental externalities, labor costs, employment, etc. criteria evaluation is important in selecting FV location. Environmental sustainability and social dimensions are becoming important criteria for companies in logistics. The purpose of the study is to determine/model the criteria interaction and also determine the criteria priorities in the FV location selection process. Meanwhile, the study aims to evaluate these criteria and present information to researchers and decision makers.Design/methodology/approachSix main criteria and 29 sub-criteria are selected from related literature. Decision making trial and evaluation laboratory (DEMATEL) method is used for determining/modeling the criteria interaction and sketching interaction diagram, and the Analytical Hierarchy Process (AHP) method is used for determining the criteria priorities. One/two-way pairwise compared main/sub-criteria views are obtained from 48 experts for calculations.Findings“Trade potential”, “transportation networks” and “economic factors” have the highest priorities, respectively, out of six main criteria, and they have the most powerful interactions that put these criteria to the center of decision process. Sub-criteria of “foreign trade potential”, “proximity to the port”, “market opportunities” and “proximity to the railway” out of 29 have a total 36.42% priority, more than one-third of the importance.Originality/valueCriteria are evaluated in FV location selection for FV sustainability using criteria interaction diagrams, affecting/being affected by the level of each criterion and their priorities. This study shows a hybrid derivation from DEMATEL-AHP usage methods together. High-volumed and qualified/experienced expert group judgments in Turkey are evaluated.

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