Best-worst multi-criteria decision-making method: A robust approach

Sadjadi, Seyed Jafar; Karimi, Mahdi

doi:10.5267/j.dsl.2018.3.003

Cited by 57 publications

(29 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Also, the behavior of the proposed model for the scenarios caused by the sensitivity analysis of the demand parameter indicates the proper functionality of the proposed model. As for future research, it is suggested to use new MADM methods such as robust BWM [69] and fuzzy BWM [70] to evaluate suppliers, and because the model presented here is placed in the NP-hard issues category it is recommended to use large-scale algorithms to solve large-scale problems. : Table 1.…”

Section: Resultsmentioning

confidence: 99%

A fuzzy solution approach for supplier selection and order allocation in green supply chain considering location-routing problem

2019

View full text Add to dashboard Cite

In the field of supply chain, selecting a suitable green supplier could significantly help us to decrease the cost and the risk involved in the operations as well as increase in the quality and green. In this paper, we develop an integrated two-stage approach based on fuzzy analytic hierarchy process (FAHP) and multi-objective mixed-integer linear programming to select suppliers and order allocation in green supply chain. In the first stage, suppliers are evaluated using FAHP method, and in the second stage, a multi-product multi-period supply chain considering green location-routing problem, discounting, and time window under uncertainty is developed. Then, a fuzzy solution approach is applied to solve proposed model using the data of a pharmaceutical chain in Iran. Results will verify the efficiency of the proposed model. [38], Ware et al. [39], Chai et al. [40], Igarashi et al. [41], Govindan et al. [42], Zimmer et al. [43] and Keshavarz Ghorabaee et al. [44]. Studies in the field of supplier selection can be mainly divided into three categories: supplier evaluation and selection, order allocation and combination of both [3]. In this research, the papers on the Green Supplier Selection and Order allocation are reviewed. Mafakheri et al. [45] used the AHP to determine the criteria weights and obtain the suppliers' scores. They also used a bi-objective mathematical model and a solution approach based on dynamic programming for order allocation. The objective functions simultaneously minimize costs and maximizes the purchase value. Four main criteria of price, delivery, quality and environmental performance were defined for supplier evaluation. Shaw et al. [46] presented a combined approach based on FAHP and fuzzy MOLP for supplier selection and order allocation problem towards minimizing greenhouse gas emissions. They applied the model on garment manufacturing company in India as for model validation. Kannan et al. [13] developed an integrated approach based on FAHP, FTOPSIS and MOLP for supplier selection and order allocation in a green supply chain management. They measured the performance of each supplier based on the cost, quality, delivery, technology capability and environmental competency criteria, using the combination of FAHP and FTOPSIS methods. Then, the resulted scores were used as a factor in the objective function of maximizing purchases from the fitting suppliers. The other objective function was to minimize total cost of purchasing. Using three environmental criteria including environmental management system, pollution and greenhouse emissions, along with other criteria, Azadnia et al. [47] utilized the FAHP method to evaluate suppliers. They developed a multi-objective programming model for allocating orders to suppliers. Govindan and Sivakumar [14] proposed a MOLP model for simultaneously minimizing costs, minimizing defective product purchases, minimizing delays in products delivery, minimizing recycling losses, and minimizing carbon emissions. They used fuzzy TOPSIS method to calculate th...

show abstract

Section: Resultsmentioning

confidence: 99%

A fuzzy solution approach for supplier selection and order allocation in green supply chain considering location-routing problem

2019

View full text Add to dashboard Cite

show abstract

“…Best-Worst method (BWM) is a recent Multi-Criteria Decision-Making (MCDM) method, developed to reduce the complexity of pairwise criteria in the AHP (Analytic Hierarchy Process) method [48][49][50][51][52][53]. Compared to AHP, BWM uses less comparison (BWM= 2n − 3, AHP= n(n − 1)/2), yet the consistency is better [48,54]. BWM is used to solve various problems, namely, supplier selection [55], location selection [50,53,56], service quality improvement [57], product design selection [49,58,59], supply-chain management [60], and performance evaluation [52,61].…”

Section: Step 4: Best-worst Methodsmentioning

confidence: 99%

On LSP Lifecycle Model to Re-design Logistics Service: Case Studies of Thai LSPs

2020

View full text Add to dashboard Cite

Improving service logistics is crucial in order to reciprocate customer needs. The paper aims to validate the Logistics Service Provider (LSP) Lifecycle Model for re-designing logistics service in three LSP case studies in Thailand. The lifecycle-stage evaluation was adapted to identify the current status in its lifecycle. Afterward, logistics service strategies were implemented according to the voice of the customer by Quality Function Deployment (QFD). The study combined the Logistics Service Provider (LSP) Lifecycle Model with the application of Industry 4.0 (I4.0) to improve service logistics. Case studies showed the implementation of the service logistics strategies with the feasibility solution of Industry 4.0.Sustainability 2020, 12, 2394 2 of 17 real-time information, and Circular Economy (CE) [21] are now among the basic customer requirements. Furthermore, customer behavior has changed too. Quick and immediate responses are expected. Information Technology (IT) has been increasingly used in the global business to satisfy the customer in terms of supply [22,23]. Today, Industry 4.0 is being used to accomplish the customer target, operation, and improvement in manufacturing [24,25]. Some examples of the advancement of Industry 4.0 are applying to self-learning automation, big data analytics, real-time information, Internet of Things (IoT), and smart sensors [26,27]. This improvement expands to the logistics industry in the form of, for example, on-demand delivery which offers an abrupt response to the customer [28,29]. The trend has changed rapidly around the world and the logistics service is demanded to support it. Therefore, LSPs need to innovate and create new service to address these complicated customer trends [30]. This paper demonstrates the use of the LSP Lifecycle Model to re-design the logistics service using three case-study LSPs in Thailand. It aims to address the research questions of whether the developed LSP Lifecycle Model is valid and if the Industry 4.0 concept is applicable and can be beneficial for LSPs. Firstly, the study identified the stage of the service. Secondly, services were re-designed using QFD. Thirdly, customer requirements were prioritized using the Multiple-Criteria Decision-Making (MCDM) tool. Finally, the Industry 4.0 concept was mapped to address these demands. Literature Review

show abstract

“…BWM somehow is also a link to connect these two perspectives in weighting criteria and this research study attempted to work on this idea to check the results of SWARA and BWM methods in a single framework. During the past few years, there have been a significant number of studies associated with the applications of SWARA and BWM implementations which can be found in References [59,60].…”

Section: Comparative Methodologiesmentioning

confidence: 99%

Comparative Evaluation of Sustainable Design Based on Step-Wise Weight Assessment Ratio Analysis (SWARA) and Best Worst Method (BWM) Methods: A Perspective on Household Furnishing Materials

Zolfani

Chatterjee

2019

Symmetry

View full text Add to dashboard Cite

For a few years, there has been an increasing consciousness to design structures that are concurrently economic and environmentally responsive. Eco-friendly inferences of building designs include lower energy consumption, reduction in CO2 emissions, assimilated energy in buildings and enhancement of indoor air quality. With the aim of fulfilling design objectives, designers normally encounter a situation in which the selection of the most appropriate material from a set of various material alternatives is essential. Sustainability has been developing as a new concept in all human activities to create a better balance between social, environmental and economic issues. Designing materials based on the sustainability concept is a key step to enable a better balance because there is no need to re-structure phases and procedures to make the system more efficient in comparison to previous models. Some of the most commonly used materials are household furnishing materials, which can be electrical devices, kitchen gears or general furnishing materials. The volume of production and consumption of these materials is considerable, therefore a newer sustainable plan for a better designed system is justifiable. In the literature, the application of multi-attribute decision-making (MADM) methods has been found to be very suitable for evaluating materials and developing general plans for them. This study contributes by applying two approaches based on MADM methods for weighting the criteria related to the sustainable design of household furnishing materials. Step-Wise Weight Assessment Ratio Analysis (SWARA) and Best Worst Method (BWM) are two specialized and new methods for weighting criteria with different approaches. This paper has not only investigated the weighting of important and related criteria for sustainable design but has also evaluated the similarities and differences between the considered weighting methods. A comparative study of SWARA and BWM methods has never been conducted to date. The results show that, except pairwise comparisons, SWARA and BWM are certainly similar and in some cases SWARA can be more accurate and effective.

show abstract

Best-worst multi-criteria decision-making method: A robust approach

Cited by 57 publications

References 24 publications

A fuzzy solution approach for supplier selection and order allocation in green supply chain considering location-routing problem

A fuzzy solution approach for supplier selection and order allocation in green supply chain considering location-routing problem

On LSP Lifecycle Model to Re-design Logistics Service: Case Studies of Thai LSPs

Comparative Evaluation of Sustainable Design Based on Step-Wise Weight Assessment Ratio Analysis (SWARA) and Best Worst Method (BWM) Methods: A Perspective on Household Furnishing Materials

Contact Info

Product

Resources

About