Comparison and evaluation of multi-criteria supplier selection approaches: A case study

A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection

Supplier selection is one of the key activities of purchase management in supply chain. Supplier selection is a multifaceted problem relating qualitative and quantitative multi-criteria. This paper deals with a supplier selection problem in an Indian automobile company. The work presents selection of headlamp supplier using integrated fuzzy multi-criteria decision-making approaches: analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). The selection process starts with identifying the criteria based on literature review and interviewing industry experts. Weights to criteria are assigned using AHP, and suppliers are ranked using AHP and TOPSIS. Consistency tests are carried out to check the quality of expert's inputs. Also, sensitivity analysis is done to check the robustness of the approach. The results address that fuzzy approaches could be effective and more accurate than the existing approaches for supplier selection problems.

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.

A comparison between fuzzy AHP and fuzzy TOPSIS methods to software requirements selection

Steel is one of the most powerful industries globally, and the associated products have a tremendous impact on nurturing a sustainable society. Considering environmental concerns within this industry's supply chain is highly successful in saving both energy and natural resources and lowering greenhouse gas emissions. In light of this, sustainable suppliers are considered input partners who play a specific role in the chain of business operations of every enterprise, maintaining them to achieve higher levels of customer satisfaction and thus gain more market share. Supplier selection can be characterized as a multi-criteria decision-making (MCDM) problem under a vague and uncertain environment. In this paper, a hybrid model of fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) is suggested to determine the most potent green supplier of steel manufacturing in Vietnam based on a complete set of five main criteria (price, quality, delivery, service, environment) through literature review and experts' responses. The significance of each criterion is measured by experts' judgments in linguistic terms, which can be expressed in triangular fuzzy numbers using the FAHP model. Then, the FTOPIS model is deployed to rank alternatives. A case study of Vietnam's top 10 steel manufacturers is implemented to exhibit the model's effectiveness. From FAHP findings, "lead time", "warranty", "defect rate", "supply capacity", and "product price" were recognized as the most impactful criteria. As for the ranking of sustainable suppliers, "Hoa Phat Group Joint-stock company", "Hoa Sen Group", and "Pomina Steel Corporation" are the top three optimal suppliers. In dealing with qualitative data and input uncertainties in the supplier evaluation and selection problem, this paper can suggest more possible solutions and provide significant materials in similar outsourcing selection problems and applications of relevant industries.

With a growing global awareness of environmental protection, green production has become an important issue for almost all manufacturers. Supplier evaluation and selection has been a critical strategic concern for long time. A green supplier selection system is therefore necessary to determine the suitability of suppliers to cooperate with the company. Researchers have developed many decision-making (DM) models to handle the green supplier evaluation and selection problem. In this paper, we conducted a comprehensive analysis of ten-literature review on DM models for solving Green Supplier Evaluation and Selection (GSES) problem. The review is focused entirely on 1098 research articles published in academic journals between 1990 and 2020 and 271 DM models divided into 170 single models and 101 combined models were reviewed, our study focused just on the single models. The analysis of the ten review show that the Analytic hierarchy process (AHP) model is the prominent DM technique (160 articles are used them) followed by Data envelopment analysis (DEA), which 122 papers apply them to achieve this goal and 101 researches which utilized Technique for order performance by similarity to ideal solution (TOPSIS) model. As a result, the AHP, DEA and TOPSIS are the most popular DM models used to solve the green supplier evaluation and selection problem.

The research aimed to determine the appropriate weight criteria and sub-criteria in selecting the chemical solvent supplier. It was also to recommend the best alternative suppliers using a comparative analysis method of Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). The research was conducted in one of the chemical manufacturing companies in Indonesia. The type of research was descriptive with a quantitative approach that used primary data sources such as questionnaires, interviews, and observations, and secondary data such as books and journals. The criteria studied were cost, quality, delivery, flexibility, supplier profile, and supplier relationship. The results of using FAHP indicate that the criteria with a major influence on the decision making of supplier selection are quality followed by delivery, cost, supplier relationship, flexibility, and supplier profile in sequence. Then, using FTOPSIS, it recommends that the best supplier alternative decision is Supplier A with a weight value of 0,773 and an approved evaluation status. The results have shown that both methods are suitable for supplier selection, particularly in supporting group decision making and modeling uncertainty.

Supplier selection and order allocation with green criteria: An MCDM and multi-objective optimization approach

Environmental concerns around the world necessitate manufacturing firms to embrace new practices that may lessen the negative environmental effect. These days, green supply chain management (GSCM) is gaining more popularity in the manufacturing sector from material acquisition to product delivery to the customers. Adoption of GSCM by Indian manufacturing firms is comparatively slow due to a lack of identification of different barriers and drivers of GSCM. To this end, the present study aims at the identification of barriers and drivers of GSCM, typical to the Indian scenario. Individual groups of six barriers and eight drivers have been identified for this research by industry experts. In addition, the study prioritizes these enabling factors using multi-criteria decision-making (MCDM) processes such as the analytic hierarchy process (AHP) approach and the technique for order of preference by similarity to ideal solution (TOPSIS) approach. In order to handle the ambiguity in decision-making, the data have been extracted from the experts using linguistic terms. A case of an Indian paper manufacturing firm is considered for this study. The fuzzy AHP (F_AHP) model indicates financial implication and lack of awareness/participation in GSCM as first and last ranked barriers, respectively, whereas the fuzzy TOPSIS (F_TOPSIS) model indicates economic consideration and customer, market and societal pressure as first and last ranked drivers, respectively. Finally, to encapsulate the robustness of the final result, sensitivity analysis has been carried out. This research will undoubtedly assist policymakers in developing policies that will facilitate GSCM implementation.

<span lang="EN-US">This paper proposes a method to rank the loads in the microgrid by means of a weight that combines the criteria together in terms of both technical and economic aspects. The fuzzy analytic hierarchy process technique for order of preference by similarity to ideal solution (fuzzy AHP TOPSIS) algorithm is used to calculate this combined weight. The criteria to be considered are load importance factor (LIF), voltage electrical distance (VED) and voltage sensitivity index (VSI). The fuzzy algorithm helps to fuzzy the judgment matrix of the analytic hierarchy process (AHP) method, making it easier to compare objects with each other and remove the uncertainty of the AHP method. The technique for order of preference by similarity to ideal solution (TOPSIS) algorithm is used to normalize the decision matrix, determine the positive and negative ideal solutions to calculate the index of proximity to the ideal solution, and finally rank all the alternatives. The combination of fuzzy AHP and TOPSIS algorithms is the optimal combination for decision making and ranking problems in a multi-criteria environment. The 19-bus microgrid system is applied to calculate and demonstrate the effectiveness of the proposed method.</span>

The plastic industry is considered one of the most dynamic industries with the highest competitive projection in the country [1]. Thanks to the advances of this industry, new products have been developed with various applications at industrial, commercial, service levels, and society’s daily lives. Plastics are highly demanded their chemical and physical properties, versatility, and low cost. However, many challenges are arising from the growth in consumption and the dynamics of the plastics industry, such as the prices of raw materials, substitute products of plastic, the demands of consumers, government, and other interested parties with the impact of plastics on the environment during the different stages of their life cycle. Concerning the life cycle of the plastic products is especially determinant the post-consumption, where plastic waste presents a low percentage of recycling and a prolonged period of degradation, being a product questioned for its negative environmental implications. In this sense, companies in the sector must implement different strategies and tools to evaluate their environmental performance, considering the product life cycle. In the world, there are various government regulations for the responsible use of plastics. International methodologies focused on sustainable environmental management in the products, processes, and organizational level have also been developed, such as the product life cycle approach, reverse logistics, and the ISO 45001 standard. However, it is necessary to create objective and analytical methodologies for evaluating environmental management and reverse logistics that provide solutions for the plastic industry, helping companies comply with applicable legal requirements and standards, and supporting decision-making processes. Concerning the decision-making is a complex process given the complexity of the sector and the multiple criteria taken into account when evaluating and establishing improvement strategies. In the literature review, we found several studies with the application of a multicriteria combined approach focused on selecting plastic recycling methods, location of plastic processing centers, eco-design of plastic products, and selection of suppliers. Despite these considerations, the research-oriented on applying integrated methodologies for evaluating performance in the environmental management and reverse logistics in the plastic industry, under multiple criteria and uncertainty, are mostly limited and with the exciting potential of development. Therefore, this document presents a hybrid methodology for evaluating the performance in the environmental management and reverse logistics in the plastic industry by applying two techniques of Multi-criteria Decision Methods (MCDM) uses in environments under uncertainly. First, the fuzzy Analytic Hierarchy Process (FAHP) is applied to estimate the initial relative weights of criteria and sub-criteria. The fuzzy set theory is incorporated to represent the uncertainty in the judgments of decision-makers. Then, the Decision-making Trial and Evaluation Laboratory (DEMATEL) was used for evaluating the interdependences between criteria and sub-criteria. FAHP and DEMATEL are later combined for calculating the final criteria and sub-criteria weights under vagueness and interdependence. Subsequently, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to rank the companies of the plastic industry. Finally, we detect improvement opportunities for the companies of the plastic sector.

A seleção de fornecedores é considerada a atividade mais crítica da função de compras e impacta diretamente a qualidade dos produtos manufaturados e o desempenho do comprador. Na literatura acadêmica, dezenas de métodos de tomada de decisão multicritério vêm sendo explorados para apoiar a seleção de fornecedores. Dentre esses, o TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) e o Fuzzy-TOPSIS (uma adaptação do primeiro) se destacam por sua simplicidade de uso e pela capacidade de avaliar um número ilimitado de alternativas e critérios simultaneamente. Embora muitos autores sugiram a adoção do TOPSIS e do Fuzzy-TOPSIS para suportar a seleção de fornecedores, na literatura não são discutidas as reais vantagens de uso e as limitações destes métodos quando aplicados neste domínio de problema. Diante de tal lacuna, este estudo compara o TOPSIS e o Fuzzy-TOPSIS, em relação à complexidade computacional, à estrutura dos algoritmos e aos resultados fornecidos quando aplicados em um mesmo caso real de seleção de fornecedores. Os métodos foram implementados usando MATLAB(r) e aplicados na seleção de fornecedores de uma empresa de cabos de transmissão. Os resultados mostram que o TOPSIS requer menor esforço para coleta de dados e processamento computacional. Em contrapartida, o Fuzzy-TOPSIS não sofre inversões no ranking e se mostra adequado para lidar com informações qualitativas e imprecisas. Os resultados deste estudo podem orientar pesquisadores e profissionais na escolha do método mais adequado para lidar com o problema de seleção de fornecedores em questão.

Objectives: User review is recognized as an effective way to promote a product or service. These reviews may be presents in different platforms such as blog, review site, social networking site, and messaging instance site. Methods: Selection of the best platform among different alternatives is called as Multi Criteria Decision Analysis/Method (MCDM) method. Objective is to select an effective platform for review. Fuzzy Analytic Hierarchy Process (AHP) is used for ranking and determines effective platform for reviews. It uses multiple criteria for making decision. In this research, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used which improves the quality of decision making for ranking alternative. Findings: When comparing with Fuzzy AHP method Fuzzy TOPSIS has an adequacy to include and exclude the criteria and alternative, which may change over a period of time. There is no restriction in number of criteria when we use the Fuzzy TOPSIS method. For future enhancements of this project can be done by using either fuzzy Analytic Network Process (ANP) or Aggregated Indices Randomization Method (AIRM) or can use hybrid method combination of any MCDM technique to rank the platform for product review. Applications: Fuzzy TOPSIS is useful for movie and product review and also we can apply this technique in uncertain situation.Keywords: electronic Word Of Mouth (eWOM), Fuzzy Analytic Hierarchy Process (AHP), Fuzzy Scale, Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Multi Criteria Decision Analysis/Method (MCDM), VIKOR

- Facility location is an integral part of the strategic planning process of almost every organization. Selecting the right location for software systems facilities involves considering various factors to ensure optimal performance, reliability, and cost-effectiveness. For business success, and competitive advantage there are some critical factors that very highly affect facility location. They are proximity to customers, infrastructure, labor quality, total cost, suppliers, etc. The criteria for selecting a facility location may be vaguely defined or open to interpretation. External factors such as economic conditions, political stability, and environmental risks may introduce vagueness and unpredictability into facility location decisions. These factors are often beyond the control of decision-makers but can have significant implications for the success of software systems. In this paper we apply fuzzy AHP-TOPSIS hybrid method for facility location in software systems. This offered model combines the fuzzy AHP and the fuzzy TOPSIS methods. Fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) are both decision-making methods commonly used in facility location selection. AHP helps in structuring a decision problem into a hierarchy of criteria and alternatives, while TOPSIS ranks alternatives based on their distance to the ideal solution. In the first part of the facility location selection process, we use fuzzy AHP method for determining weights of criteria that are important in selection process. Then by using fuzzy TOPSIS we rank alternatives and select appropriate location for facility.

Facility location is an integral part of the strategic planning process of almost every organization. Selecting the right location for software systems facilities involves considering various factors to ensure optimal performance, reliability, and cost-effectiveness. For business success, and competitive advantage there are some critical factors that very highly affect facility location. They are proximity to customers, infrastructure, labor quality, total cost, suppliers, etc. The criteria for selecting a facility location may be vaguely defined or open to interpretation. External factors such as economic conditions, political stability, and environmental risks may introduce vagueness and unpredictability into facility location decisions. These factors are often beyond the control of decision-makers but can have significant implications for the success of software systems. In this paper we apply fuzzy AHP-TOPSIS hybrid method for facility location in software systems. This offered model combines the fuzzy AHP and the fuzzy TOPSIS methods. Fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) are both decision-making methods commonly used in facility location selection. AHP helps in structuring a decision problem into a hierarchy of criteria and alternatives, while TOPSIS ranks alternatives based on their distance to the ideal solution. In the first part of the facility location selection process, we use fuzzy AHP method for determining weights of criteria that are important in selection process. Then by using fuzzy TOPSIS we rank alternatives and select appropriate location for facility.