Received March 1, 2020 Revised May 10, 2020 Accepted May 25, 2020 In recent decades, due to the rapid consumption of natural resources and the need for environmental protection, sustainability in supply chain management has emerged as an increasingly important issue. Therefore, in this study, supplier selection has been performed in order to achieve sustainability, taking into account all aspects: economic, social and environmental criteria. For this purpose, combined FUCOM Rough SAW approach has been used. The evaluation of criteria grouped at two levels has been carried out by decision makers according to the needs of the company whose main activity is lime production. To obtain the criterion weight values, the FUCOM (FUll COnsistency Method) has been used.. In order to avoid uncertainty and imprecision in the supplier evaluation process, combination with the Rough SAW method, which is used for ranking and supplier selection, has been performed. In order to control the stability of the used model, a sensitivity analysis has been performed. The first phase involves changing the weights of the criteria, while the second phase involves a comparative analysis using other MCDM methods.

Third-party logistics (3PL) has involved a significant response among researchers and practitioners in the recent decade. In the global competitive scenario, multinational companies (MNCs) not only improve the quality of the service and increase efficiency, but they also decrease costs by means of 3PL. However, the assessment and selection of 3PL is a very critical decision to make, comprising intricacy due to the existence of various imprecisely based criteria. Also, uncertainty is an unavoidable part of information in the decision-making process and its importance in the selection process is relatively high and needs to be carefully considered. Consequently, incomplete and inadequate data or information may occur among other various selection criteria, which can be termed as a multi-criteria decision-making (MCDM) problem. Rough numbers are very flexible to model this type of uncertainty occurring in MCDM problems. In this paper, the Hamy Mean (HM) operator and Dombi operations are expanded by rough numbers (RNs) so as to propose the Rough Number Dombi-Hamy Mean (RNDHM) operator. Then, the Multi-Attribute Decision-Making (MADM) model is designed with the RNDHM operator. Finally, the RNDHM is employed to achieve the final ranking of the 3PL providers.

A decision-making process requires a prior definition and fulfilment of certain factors, especially when it refers to complex fields such as supply chain management. One of the most important items in the initial stage of a supply chain, which strongly influences its further flow, is making a decision on the most suitable supplier. In this paper, a model for evaluation and supplier selection has been proposed, which has been considered in more than ten different production areas. The model consists of twenty quantitative and qualitative criteria, which are reduced to a total of nine by the application of the fuzzy AHP and the assessment of managers in production companies. The verification of the model has been presented throughout a selection of suppliers in a company for the production of plastic bags and foils, where the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method has been used to determine the significance of the criteria, and the Fuzzy Evaluation based on Distance from Average Solution (Fuzzy EDAS) to evaluate and select suppliers. The obtained results have been considered throughout a sensitivity analysis in which a total of 15 different scenarios have been formed and where the stability of the model has been determined, since the supplier one is the best solution in all the cases.

The daily requirements and needs imposed on the executors of logistics services imply the need for a higher level of quality. In this, the proper execution of all sustainability processes and activities plays an important role. In this paper, a new methodology for improving the measurement of the quality of the service consisting of three phases has been developed. The first phase is the application of the Delphi method to determine the quality dimension ranking. After that, in the second phase, using the FUCOM (full consistency method), we determined the weight coefficients of the quality dimensions. The third phase represents determining the level of quality using the SERVQUAL (service quality) model, or the difference between the established gaps. The new methodology considers the assessment of the quality dimensions of a large number of participants (customers), on the one hand, and experts’ assessments on the other hand. The methodology was verified through the research carried out in an express post company. After processing and analyzing the collected data, the Cronbach alpha coefficient for each dimension of the SERVQUAL model for determining the reliability of the response was calculated. To determine the validity of the results and the developed methodology, an extensive statistical analysis (ANOVA, Duncan, Signum, and chi square tests) was carried out. The integration of certain methods and models into the new methodology has demonstrated greater objectivity and more precise results in determining the level of quality of sustainability processes and activities.

The functioning of each traffic system depends to a great extent on the way the rail transport system operates. Taking into account the aspect of market turbulence and the dependence on adequate delivery when it comes to freight transport and traffic in accordance with a yearly Timetable in passenger traffic, transport policies are changing with time. Therefore, this document is considering the railway management models on the territory of Bosnia and Herzegovina. For the purpose of evaluating these models, a new hybrid model has been applied, i.e. the model which includes a combination of the Delphi, SWARA (Step-Wise Weight Assessment Ratio Analysis) and MABAC (Multi-Attributive Border Approximation Area Comparison) methods. In the first phase of the study, the criteria ranking was determined based on 16 expert grades used in the Delphi Method. After that, a total of 14 decision-makers determined the mutual criteria impact, which is a prerequisite for the application of the SWARA Method used to determine the relative weight values of the criteria. The third phase involves the application of the MABAC Method for evaluating and determining the most suitable variant. In addition, a sensitivity analysis involving the application of the ARAS, WASPAS, SAW and EDAS methods has been performed, thus verifying the previously obtained variant ranking.

The inconsistency of phytogenic feed additives’ (PFA) effects on the livestock industry poses a risk for their use as a replacement for antibiotic growth promoters. The livestock market is being encouraged to use natural growth promotors, but information is limited about the PFA mode of action. The aim of this paper is to present the complexity of compounds present in essential oils (EOs) and factors that influence biological effects of PFA. In this paper, we highlight various controls and optimization parameters that influence the processes for the standardization of these products. The chemical composition of EOs depends on plant genetics, growth conditions, development stage at harvest, and processes of extracting active compounds. Their biological effects are further influenced by the interaction of phytochemicals and their bioavailability in the gastrointestinal tract of animals. PFA effects on animal health and production are also complex due to various EO antibiotic, antioxidant, anti-quorum sensing, anti-inflammatory, and digestive fluids stimulating activities. Research must focus on reliable methods to identify and control the quality and effects of EOs. In this study, we focused on available microencapsulation techniques of EOs to increase the bioavailability of active compounds, as well as their application in the animal feed additive industry.

Making a decision in everyday life always comes with uncertainty and responsibility. To reduce the risk to a minumum and in order to make a right decision a person can use methods of multicriteria analysis in combination in fuzzy logic. A married couple, representing decision makers in this case study, have purchased an apartment and it needs to be completely refurbished including outside carpentry. Aim of this study is to select the most suitable manufacturer of PVC carpentry for apartment refurbishing. A total pool of 14 quantitative and qualitative criteria is used as a base for selection of the most suitable of seven available manufacturers. For this case study we will use one of newer methods of multicriteria analysis of fuzzy Evaluation Based on Distance from Average Solution (fuzzy EDAS) method. Having reached the results, an analysis of sensitivity has been conducted showing stability of results where manufacturer number 4 represents an optimal solution in 13 experimental sets out of 14 total. DOI: http://dx.doi.org/10.5755/j01.ee.29.3.16818

The decision-making process requires the prior definition and fulfillment of certain factors, especially when it comes to complex areas such as supply chain management. One of the most important items in the initial phase of the supply chain, which strongly influences its further flow, is to decide on the most favorable supplier. In this paper a selection of suppliers in a company producing polyvinyl chloride (PVC) carpentry was made based on the new approach developed in the field of multi-criteria decision making (MCDM). The relative values of the weight coefficients of the criteria are calculated using the rough analytical hierarchical process (AHP) method. The evaluation and ranking of suppliers is carried out using the new rough weighted aggregated sum product assessment (WASPAS) method. In order to determine the stability of the model and the ability to apply the developed rough WASPAS approach, the paper analyzes its sensitivity, which involves changing the value of the coefficient λ in the first part. The second part of the sensitivity analysis relates to the application of different multi-criteria decision-making methods in combination with rough numbers that have been developed in the very recent past. The model presented in the paper is solved by using the following methods: rough Simple Additive Weighting (SAW), rough Evaluation based on Distancefrom Average Solution (EDAS), rough MultiAttributive Border Approximation area Comparison (MABAC), rough Visekriterijumsko kompromisno rangiranje (VIKOR), rough MultiAttributiveIdeal-Real Comparative Analysis (MAIRCA) and rough Multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA). In addition, in the third part of the sensitivity analysis, the Spearman correlation coefficient (SCC) of the ranks obtained was calculated which confirms the applicability of all the proposed approaches. The proposed rough model allows the evaluation of alternatives despite the imprecision and lack of quantitative information in the information-management process.

Ensuring costs reduction and increasing competitiveness and satisfaction of end users are the goals of each participant in the supply chain. Taking into account these goals, the paper proposes methodology for defining the most important criteria for suppliers’ evaluation. From a set of twenty established criteria, i.e. four sets of criteria: finances, logistics, quality and communication and business including its sub-criteria, we have allocated the most important ones for supplier selection. Analytic Hierarchy Process (AHP) based on rough numbers is presented to determine the weight of each evaluation criterion. For the criteria evaluation we have used knowledge from the expert in this field. The efficacy of the proposed evaluation methodology is demonstrated through its application to the company producing metal washers for the automotive industry. Next a sensitivity analysis is carried out in order to show the stability of the model. For checking stability the AHP method in conventional form is used in combination with fuzzy logic.