A NEW LOGARITHM METHODOLOGY OF ADDITIVE WEIGHTS (LMAW) FOR MULTI-CRITERIA DECISION-MAKING: APPLICATION IN LOGISTICS

Logistics management has been playing a significant role in ensuring competitive growth of industries and nations. This study proposes a new Multi-Criteria Decision-making (MCDM) framework for evaluating operational efficiency of logistics service provider (LSP). We present a case study of comparative analysis of six leading LSPs in India using our proposed framework. We consider three operational metrics such as annual overhead expense (OE), annual fuel consumption (FC) and cost of delay (CoD, two qualitative indicators such as innovativeness (IN) which basically indicates process innovation and average customer rating (CR)and one outcome variable such as turnover (TO) as the criteria for comparative analysis. The result shows that the final ranking is a combined effect of all criteria. However, it is evident that IN largely influences the ranking. We carry out a comparative analysis of the results obtained from our proposed method with that derived by using existing established frameworks. We find that our method provides consistent results; it is more stable and does not suffer from rank reversal problem

A Review of the Criteria and Methods of Reverse Logistics Supplier Selection

This article presents a literature review on reverse logistics (RL) supplier selection in terms of criteria and methods. A systematic view of past work published between 2008 and 2020 on Web of Science (WOS) databases is provided by reviewing, categorizing, and analyzing relevant papers. Based on the analyses of 41 articles, we propose a three-stage typology of decision-making frameworks to understanding RL supplier selection, including (a) establishment of the selection criteria; (b) calculation of the relative weights and ranking of the selection criteria; (c) ranking of alternatives (suppliers). The main discoveries of this review are as follows. (1) Attention to the field of RL supplier selection is increasing, as evidenced by the increasing number of papers in the field. With the adaption of circular economy legislation and the need resource and business resilience, it is expected that RL and RL supplier selection will be a hot topic in the near future. (2) A large number of papers take “sustainability” as the theoretical approach to carry out research and use it as the basis for determining the criteria. (3) Multi-criteria decision making (MCDM) methods have been widely used in RL supplier selection and have been constantly innovated. (4) Artificial intelligence methods are also gradually being applied. Finally, gaps in the literature are identified to provide directions for future research. (5) Value-added service is underrepresented in the current study and needs further attention

An Integrated Multicriteria Decision-Making Approach for Collection Modes Selection in Remanufacturing Reverse Logistics

Reverse logistics (RL) is closely related to remanufacturing and could have a profound impact on the remanufacturing industry. Different from sustainable development which is focused on economy, environment and society, circular economy (CE) puts forward more requirements on the circularity and resource efficiency of manufacturing industry. In order to select the best reverse logistics provider for remanufacturing, a multicriteria decision-making (MCDM) method considering the circular economy is proposed. In this article, a circularity dimension is included in the evaluation criteria. Then, analytic hierarchy process (AHP) is used to calculate the global weights of each criterion, which are used as the parameters in selecting RL providers. Finally, technique for order of preference by similarity to ideal solution (TOPSIS) is applied to rank reverse logistics providers with three different modes. A medium-sized engine manufacturer in China is taken as a case study to validate the applicability and effectiveness of the proposed framework

Uncertainty Models in Reverse Supply Chain: A Review

Reverse logistic has become an important topic for the organization due to growing environmental concern, government regulation, economic value, and sustainable competitiveness. Uncertainty is one of the key factors in the reverse supply chain that must be controlled; thus, the company could optimize the reverse supply chain function. This paper discusses progress in reverse logistic research. A total of 72 published articles were selected, analyzed, categorized and the research gaps were found among them. The study began by analyzed previous research articles in reverse logistic. In this stage, we also collected and reviewed journals discussing about the reverse supply chain. Meanwhile, the result of this stage shows that uncertainty factor has not been reviewed in detail. The most common theme as the background research in reverse logistic is environmental and economic aspect. Uncertainty in Close Loop Supply Chain is the most widely used approach, followed by the usage on reverse logistics, reverse supply chain and reverse Model. The most used approach and method on uncertainty are Mixed Integer Linear Programing, mixed integer nonlinear Programing, Robust Fuzzy Stochastic Programming, and Improved kriging-assisted robust optimization method. Customer demand, total cost, product returns are the most widely researched aspects. This paper may be useful for academicians, researchers and practitioners in learning on reverse logistic and reverse supply chain; therefore, close loop supply chain can be guidance for upcoming researches. Research opportunity based on this research combines total cost, quality return product, truck capacity, delivery route, remanufacturing capacity, and facility location got optimum function in uncertainty. The research method and approach for MINLP, IK-MRO and RSFP provide many opportunities for research. For theme and area in reverse logistic, close loop supply chain is the theme that provides the most research opportunities

An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains

Digital supply chains (DSCs) are collaborative digital systems designed to quickly and efficiently move information, products, and services through global supply chains. The physical flow of products in traditional supply chains is replaced by the digital flow of information in DSCs. This digitalization has changed the conventional supplier selection processes. We propose an integrated and comprehensive fuzzy multicriteria model for supplier selection in DSCs. The proposed model integrates the fuzzy best-worst method (BWM) with the fuzzy multi-objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA), fuzzy complex proportional assessment of alternatives (COPRAS), and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The fuzzy BWM approach is used to measure the importance weights of the digital criteria. The fuzzy MULTIMOORA, fuzzy COPRAS, and fuzzy TOPSIS methods are used as prioritization methods to rank the suppliers. The maximize agreement heuristic (MAH) is used to aggregate the supplier rankings obtained from the prioritization methods into a consensus ranking. We present a real-world case study in a manufacturing company to demonstrate the applicability of the proposed method

Hotel selection with safe tourism certificates in Covid-19 pandemic using SWARA and fuzzy COPRAS methods

The virus, which emerged in Wuhan, China, has taken the whole world under its influence in a short time. The World Health Organization declared this period as the "pandemic period", which means a global epidemic, due to the spread of the virus to the world in a short time. This period has undoubtedly been a period when many habits changed for everyone. Vacation habit is also one of the habits that change during this period. Especially in the summer months, people who spend their holidays in hotels had to be more sensitive in choosing the hotel due to the continuation of the pandemic period. While different criteria were considered in hotel selection before, the criterion of having a safe tourism certificate has become the most important criterion due to the pandemic. Businesses with this certificate can provide service without any problems as they take all precautions during the pandemic period. In this study, a hotel selection problem that takes into account the criteria of safe tourism certificate is discussed. In this study, a hotel selection problem that takes into account the safe tourism certification criteria is discussed. In the study, Stepwise Weight Assessment Ratio Analysis (SWARA) and fuzzy logic based The Complex Proportional Assessment (COPRAS) methods were used to solve the problem of choosing the most suitable hotel. As a result of the study, ten hotel alternatives were evaluated according to the criteria of safe tourism certificate during the pandemic period and the most suitable hotel was selected

COMPARISON OF THREE FUZZY MCDM METHODS FOR SOLVING THE SUPPLIER SELECTION PROBLEM

The evaluation and selection of an optimal, efficient and reliable supplier is becoming more and more important for companies in today’s logistics and supply chain management. Decision-making in the supplier selection domain, as an essential component of the supply chain management, is a complex process since a wide range of diverse criteria, stakeholders and possible solutions are embedded into this process. This paper shows a fuzzy approach in multi – criteria decision-making (MCDM) process. Criteria weights have been determined by fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method. Chosen methods, fuzzy TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution), fuzzy WASPAS (Weighted Aggregated Sum Product Assessment) and fuzzy ARAS (Additive Ratio Assessment) have been used for evaluation and selection of suppliers in the case of procurement of THK Linear motion guide components by the group of specialists in the “Lagerton” company in Serbia. Finally, results obtained using different MCDM approaches were compared in order to help managers to identify appropriate method for supplier selection problem solving

Selection of student automation system by multi-criteria decisionmaking methods

Öğrenci işleri otomasyonu (ÖİO); öğrenci, akademisyen ve idari personel üçlüsünün koordinasyonunu sağlama görevini üstlenen ve her seviyedeki öğrencilerin üniversiteye ilk kayıttan mezun oluncaya ve mezuniyetinden sonraki süreçlerde de tüm işlemlerini yürütülebildiği yazılımlardır. ÖİO'ler, kullanıcıların performanslarını büyük ölçüde etkileyen yazılım sistemleridir. Kullanıcıların performansını artırabilmek için ÖİO'lerin etkin ve yüksek verimlilikte çalışması gerekmektedir. Bu çalışmanın amacı farklı üniversitelerde kullanılan ÖİO'lerin performanslarını ölçerek en uygun olanı belirleyebilmektir. Bu süreçte bir birlerini etkileyen bir çok kriter dikkate alındığından sorun; Çok Kriterli Karar Verme (ÇKKV) problemi olarak görülmektedir. Beş üniversitenin kullanmakta oldukları ÖİO'ler, ÇKKV yöntemlerinden SWARA (Step-wise Weight Assessment Ratio Analysis ), ARAS (Additive Ratio Assessment) ve EDAS (Evaluation based on Distance from Average Solution) yöntemleri ile değerlendirilmiştir. SWARA, ölçme kriterlerini ağırlıklandırmada; ARAS ve EDAS yöntemleri ise ÖİO'lerin performansını belirlemede kullanılmıştır. Çalışma neticesinde en önemli kriterin veritabanı güvenliği olduğu belirlenmiştir. ÖİO'lerin sıralanmasında her bir değerlendirme yöntemi aynı sonucu vermiştir.Student Affairs Automation (SAA) system is the software coordinating the trio of students, academicians, and administrative staff. These programs are used to carry out all the procedures of each student from the enrollment to the university to the graduation. SAAs are software systems that greatly affect users' performances. SAAs must work effectively and efficiently so that the users' performance can increase. The aim of this study is to determine the most appropriate SAA by measuring the performances of SAAs used in different universities. The problem is a Multi-Criteria Decision Making one as many criteria affecting each other are considered. The SAAs used by the five universities were evaluated by using SWARA (Step-wise Weight Assessment Ratio Analysis), ARAS (Additive Ratio Assessment) and EDAS (Evaluation based on Distance from Average Solution) methods. SWARA was used for weighting the measurement criteria while ARAS and EDAS methods were used to determine the performances of the SAAs. The study proved that the most important criterion was database security. Each evaluation method gave the same result in the ranking of the SAAs