Sustainable traffic system management under conditions of uncertainty and inappropriate road infrastructure is a responsible and complex task. In Bosnia and Herzegovina (BiH), there is a large number of level crossings which represent potentially risky places in traffic. The current state of level crossings in BiH is a problem of the greatest interest for the railway and a generator of accidents. Accordingly, it is necessary to identify the places that are currently a priority for the adoption of measures and traffic control in order to achieve sustainability of the whole system. In this paper, the Šamac–Doboj railway section and passive level crossings have been considered. Fifteen different criteria were formed and divided into three main groups: safety criteria, road exploitation characteristics, and railway exploitation characteristics. A novel integrated fuzzy FUCOM (full consistency method)—fuzzy PIPRECIA (pivot pairwise relative criteria importance assessment) model was formed to determine the significance of the criteria. When calculating the weight values of the main criteria, the fuzzy Heronian mean operator was used for their averaging. The evaluation of level crossings was performed using fuzzy MARCOS (measurement of alternatives and ranking according to compromise solution). An original integrated fuzzy FUCOM–Fuzzy PIPRECIA–Fuzzy MARCOS model was created as the main contribution of the paper. The results showed that level crossings 42 + 690 (LC4) and LC8 (82 + 291) are the safest considering all 15 criteria. The verification of the results was performed through four phases of sensitivity analysis: resizing of an initial fuzzy matrix, comparative analysis with other fuzzy approaches, simulations of criterion weight values, and calculation of Spearman’s correlation coefficient (SCC). Finally, measures for the sustainable performance of the railway system were proposed.

In the logistics world, special attention should be given to warehousing systems, cost rationalization, and improvement of all the factors that affect efficiency and contribute to smooth functioning of logistics subsystems. In real time industrial practice, the issue of evaluating and selecting the most appropriate forklift involves a complex decision-making problem that should be formulated through an efficient analytical model. The forklifts efficiency plays a very important role in the company. The forklifts are being used on a daily basis and no logistical processes could be done without them. Therefore, it has been decided to determine their efficiency, which will contribute to the optimization of the process in this logistics subsystem. This study puts forward an integrated forklift selection model using Data Envelopment Analysis (DEA), Full Consistency Method (FUCOM) and Measurement Alternatives and Ranking According to the Compromise Solution (MARCOS) methods. Five input parameters (regular servicing costs, fuel costs, exceptional servicing costs, total number of all minor accidents and damage caused by forklifts) and one output parameter (number of operating hours) were first identified to assess efficiency of eight forklifts in a warehousing system of the Natron-Hayat company using the DEA model. This step allows sorting of efficient forklifts which are subsequently evaluated and ranked using FUCOM and MARCOS methods. A sensitivity analysis is also performed in order to check reliability and accuracy of the results. The findings of this research clearly show that the proposed decision-making model can significantly contribute to all spheres of business applications.

There are numerous algorithms and solutions for car or object detection as humanity is aiming towards the smart city solutions. Most solutions are based on counting, speed detection, traffic accidents and vehicle classification. The mentioned solutions are mostly based on high-quality videos, wide angles camera view, vehicles in motion, and are optimized for good visibility conditions intervals. A novelty of the proposed algorithm and solution is more accurate digital data extraction from video file sources generated by security cameras in Bosnia and Herzegovina from M18 roadway, but not limited only to that particular source. From the video file sources, data regarding number of vehicles, speed, traveling direction, and time intervals for the region of interest will be collected. Since finding contours approach is effective only on objects that are mobile, and because the application of this approach on traffic junctions did not yield desired results, a more specific approach of classification using a combination of Histogram of Oriented Gradients (HOG) and Support Vector Machines (Linear SVM) has shown to be more appropriate as the original source data can be used for training where the main benefit is the preservation of local second-order interactions, providing tolerance to local geometric misalignment and ability to work with small data samples. The features of the objects within a frame are extracted first by standardizing the feature variables and then computing the first order gradients of the frame. In the next stage, an encoding that remains robust to small changes while being sensitive to local frame content is produced. Finally, the HOG descriptors are generated and normalized again. In this way the channel histogram and spatial vector becomes the feature vector for the Linear SVM classifier. With the following parameters and setup system accuracy was around 85 to 95%. In the next phase, after cleaning protocols on collected data parameters, data will be used to research asphalt deformation effects.

In multi-criteria decision-making (MCDM) problems the decision-maker is often forced to accept a not ideal solution. If the ideal choice exists, it would be certainly chosen. The acceptance of a non- ideal solution leads to some inadequate properties in the chosen solution. MCDM methods help the decision-maker to structure his needs considering different units, in which the properties of the solutions are expressed. Secondly, with MCDM tools the assessment of the available solutions can be calculated with consideration of the decision-maker’s needs. The incorporation of the cost criterion into the decision maker’s preferences calculation, and the solution assessment calculation, deprives the decision-maker of the ability to calculate the financial result of the decision he must make. A new multi-criteria decision making with cost criterion analysed at the final stage (MCDM-CCAF) method is developed based on principle of Pareto optimal decisions. It is proposed to exclude the cost criterion from the MCDM analysis and consider it at the final phase of the decision-making process. It is illustrated by example solutions with consideration of cost criterion and without it. It is proposed to apply the invented post-processing method to all MCDM analyses where the cost criterion of analysed variants is considered.

Trends of globalization very often cause the emergence of phenomena that asymmetrically affect the overall sustainability of the transport system. In order to predict certain situations and potentially be able to manage the transport system, it is necessary to manage risk situations and traffic safety in a timely manner. This study has conducted an investigation which implies defining the level of safety of a total of nine sections of two-lane roads. The main aim of the paper is to create a new multiphase model consisting of CRITIC (The CRiteria Importance Through Intercriteria Correlation), Fuzzy FUCOM (Full Consistency Method), DEA (Data Envelopment Analysis), and Fuzzy MARCOS (Measurement Alternatives and Ranking according to the COmpromise Solution) methods for determining the level of traffic safety on road sections under the conditions of uncertainty. In order for the created model to be adequately applied, eight parameters were created, and they were classified through four inputs and four outputs. To calculate the significance of the inputs, the CRITIC method based on the symmetric correlation matrix was used, and taking into account the nature of the outputs, the Fuzzy FUCOM method based on averaged values using the fuzzy Bonferroni Mean (BM) operator was applied to determine their weights. To determine the degree of safety, the DEA model was created. After that, the Fuzzy MARCOS method was used in order to determine the final ranking of the remaining five sections of the road network. Finally, the verification of results was performed through three phases of Sensitivity Analysis (SA).

Selection of Sustainable Suppliers is a key term in sustainable supply chain management. This is the reason to choose the supplier who will support the company to implement sustainability in its business, especially in the supply chain. The aim of this paper is to establish a new innovative model for decision-making based on a fuzzy approach. This decision-making problem is solved by applying multi-criteria decision-making since there are several criteria according to which a decision should be made: economic, social, and environmental. In order to make the final decision on the supply chain better and safer, the social criteria were modified in this paper, adding ethical criteria. The example with modified social criteria in this paper was shown on the example of the company "Voćar" Brčko, which deals with the production of food products. In this paper, the fuzzy Measurement Alternatives and Ranking, according to the Compromise Solution Method, was used. The findings have shown that supplier A1 has the best results, which were confirmed with the first sensitivity analysis. However, the second sensitivity analysis has shown that supplier A5 was better than supplier A1 in 14 scenarios. Due to these findings, no unanimous decision can be made about which supplier among the two, in this case, would contribute more. This paper has shown that the selection of sustainable suppliers is crucial for any company focused on the principles of sustainability in business. Moreover, this paper has shown that it is sometimes very difficult to select just one supplier.

Bosnia and Herzegovina (B&H) possess many natural resources that can be exploited for the development of medical tourism. The offer of medical tourism in B&H is focused on spa tourism. B&H has 16 registered spa-centers offering different types of services. This study provides a complete overview of the assessment of the current state of spa-centres using expert decision-making and methods of multi-criteria analysis. An innovative and novel MCDM model based on integration of the FUCOM (full consistency method) and fuzzy MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) methods was used. The model consists of 16 alternatives and eight sustainable criteria. The results of this research have shown that the spa-centers of Ilidža near Sarajevo, Fojnica and Vrućica have the best assessments of the current situation and prerequisites for sustainable business. These spa-centers should be a benchmark to other spas providing direction on how to improve their business to be more sustainable and competitive in the market. These results were confirmed by a sensitivity analysis with two approaches used. The first approach was to compare the results obtained by the fuzzy MARCOS method with other fuzzy methods, and the second approach was to examine the influence of the application of different weights on the final ranking of the spa. The results of this study can serve spa-canter managers to understand the position of their spa-centers in order to exploit advantages they have and eliminate the shortcomings to improve their business.

On the question: how to react in a particular situation, the management of the company must have a quick answer. In the time of fast and huge changes in production, the management must know what resources are available in the company and what kind of environment it faces. To respond promptly to the requirements of the environment, the company must define a clear strategy for its business. To define a strategy, management must know the state of the company. From these reasons, in this research it was conducted SWOT analysis of specific company, and after that the elements of the SWOT matrix were ranked using fuzzy PIPRECIA method. This ranking shows on which element company should pay the most attention.

In this paper, empirical research about Passenger Car Equivalents (PCEs) on the longitudinal downgrade of two-lane roads in Bosnia and Herzegovina has been conducted in order to determine the influence of vehicle structure under free traffic flow conditions. The research has been carried out considering the classes of vehicles at cross-sections on the downgrade of two-lane roads. As a result, the negative influence of vehicle structure under free traffic flow conditions using passenger car equivalents (PCEs) has been determined. The results show that on the downgrade of two-lane roads, the value of passenger car equivalent decreases from the level terrain to the boundary minimum value for the determined downgrade g = −3.00%, after which its value starts to increase slightly. Based on the obtained values, the models calibrated with a second-degree polynomial have been developed to determine the average value of passenger car equivalent as a function of its boundary value. The paper also compares the results obtained by the developed models with the models from the Highway Capacity Manual under free traffic flow conditions. In addition, models for the percentage values of PCE15%, PCE50% and PCE85% have been established.

The conditions of globalization often dictate the functioning of transport markets, so it is necessary to conduct frequent research in order to achieve sustainable business. This is achieved through adequate risk and safety management at all levels. The research carried out in this paper includes determining the state of railway traffic safety in a total of nine railway sections in Bosnia and Herzegovina (B&H). The aim of this paper is to develop a new integrated Entropy-Fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment)-DEA (Data Envelopment Analysis) model for determining the state of safety in B&H under particular conditions of uncertainty. Additionally, the aim is to combine the advantages of linear programming (DEA), an objective method (Entropy), and a subjective method (Fuzzy PIPRECIA). In this way, an integrated objective–subjective model is created that provides accurate and balanced decision-making through their integration. Eleven sustainable criteria were defined and divided into six inputs and five outputs. The Entropy model was used to determine the weight values of the inputs, while due to the nature of the outputs, Fuzzy PIPRECIA was used to evaluate them. After the application of the two methods, the way of averaging their values was defined. The DEA model, which implies an input- and output-oriented model, was applied to determine which railway sections have satisfactory performance in terms of safety. Two sections were eliminated from further computation due to extremely poor performance and high risk. Then, the weighted overall efficiency ranking method was applied to determine the final ranking of the railway sections. The results obtained were verified through a sensitivity analysis, which involved changing the impact of the five most significant criteria and a comparison with two Multi-Criteria Decision-Making (MCDM) methods.

The aim of this research is the evaluation and selection of suppliers by applying the fuzzy multi-criteria analysis. The study used fuzzy Analytic Hierarchy Process (FAHP) to choose the optimal supplier for the purchase of materials necessary for the production of pre-insulated pipes. Decision-makers selected among five suppliers based on nine criteria: material cost, pipe length, delivery time, type of payment, transport distance, quality, reliability, flexibility and relationship with customers. Effective execution of procurement, in this case, the procurement of material needed for the production logistics subsystem, influences the overall efficiency of the business. It is vital to make the right decision when selecting a supplier, because the optimal choice ensures lower cost and higher quality of the product itself, and therefore more competitiveness in the market.

The success of any activity and process depends fundamentally on the possibility of balancing (symmetry) needs and their satisfaction. That is, the ability to properly define a set of success indicators. The application of the developed new multi-criteria decision-making (MCDM) methods can be eliminated or decreased by decision-makers’ subjectivity, which leads to consistency or symmetry in the weight values of the criteria. In this Special Issue, 40 research papers and one review study co-authored by 137 researchers from 23 different countries explore aspects of multi-criteria modeling and optimization in crisp or uncertain environments. The papers proposing new approaches and elaborate case studies in the following areas of applications: MCDM optimization in sustainable engineering, environmental sustainability in engineering processes, sustainable multi-criteria production and logistics processes planning, integrated approach for modeling processes in engineering, new trends in the multi-criteria evaluation of sustainable processes, multi-criteria decision-making in strategic management based on sustainable criteria.

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.

The decision-making trial and evaluation laboratory (DEMATEL) method is one of the most significant multi-criteria techniques for defining the relationships among criteria and for defining the weight coefficients of criteria. Since multi-criteria models are very often used in management and decision-making under conditions of uncertainty, the fuzzy DEMATEL model has been extended in this paper by D numbers (fuzzy DEMATEL-D). The aim of this research was to develop a multi-criteria methodology that enables the objective processing of fuzzy linguistic information in the pairwise comparison of criteria. This aim was achieved through the development of the fuzzy DEMATEL-D method. Combining D numbers with trapezoidal fuzzy linguistic variables (LVs) allows for the additional processing of uncertainties and ambiguities that exist in experts’ preferences when comparing criteria with each other. In addition, the fuzzy DEMATEL-D methodology has a unique reasoning algorithm that allows for the rational processing of uncertainties when using fuzzy linguistic expressions for pairwise comparisons of criteria. The fuzzy DEMATEL-D methodology provides an original uncertainty management framework that is rational and concise. In order to illustrate the effectiveness of the proposed methodology, a case study with the application of the proposed multi-criteria methodology is presented.

An arbitrary univariate polynomial of nth degree has n sequences. The sequences are systematized into classes. All the values of the first class sequence are obtained by Newton’s polynomial of nth degree. Furthermore, the values of all sequences for each class are calculated by Newton’s identities. In other words, the sequences are formed without calculation of polynomial roots. The New-nacci method is used for the calculation of the roots of an nth-degree univariate polynomial using radicals and limits of successive members of sequences. In such an approach as is presented in this paper, limit play a catalytic–theoretical role. Moreover, only four basic algebraic operations are sufficient to calculate real roots. Radicals are necessary for calculating conjugated complex roots. The partial limitations of the New-nacci method may appear from the decadal polynomial. In the case that an arbitrary univariate polynomial of nth degree (n ≥ 10) has five or more conjugated complex roots, the roots of the polynomial cannot be calculated due to Abel’s impossibility theorem. The second phase of the New-nacci method solves this problem as well. This paper is focused on solving the roots of the quintic equation. The method is verified by applying it to the quintic polynomial with all real roots and the Degen–Abel polynomial, dating from 1821.