Sustainable development is one of the most important preconditions for preserving resources and balanced functioning of a complete supply chain in different areas. Taking into account the complexity of sustainable development and a supply chain, different decisions have to be made day-to-day, requiring the consideration of different parameters. One of the most important decisions in a sustainable supply chain is the selection of a sustainable supplier and, often the applied methodology is multi-criteria decision-making (MCDM). In this paper, a new hybrid MCDM model for evaluating and selecting suppliers in a sustainable supply chain for a construction company has been developed. The evaluation and selection of suppliers have been carried out on the basis of 21 criteria that belong to all aspects of sustainability. The determination of the weight values of criteria has been performed applying the full consistency method (FUCOM), while a new rough complex proportional assessment (COPRAS) method has been developed to evaluate the alternatives. The rough Dombi aggregator has been used for averaging in group decision-making while evaluating the significance of criteria and assessing the alternatives. The obtained results have been checked and confirmed using a sensitivity analysis that implies a four-phase procedure. In the first phase, the change of criteria weight was performed, while, in the second phase, rough additive ratio assessment (ARAS), rough weighted aggregated sum product assessment (WASPAS), rough simple additive weighting (SAW), and rough multi-attributive border approximation area comparison (MABAC) have been applied. The third phase involves changing the parameter ρ in the modeling of rough Dombi aggregator, and the fourth phase includes the calculation of Spearman’s correlation coefficient (SCC) that shows a high correlation of ranks.

The quality of road infrastructure largely depends on the quality of road construction and adequate construction machinery. In order to reduce uncertainties and improve the performance of road infrastructure, it is necessary to apply modern and appropriate construction machinery. The aim of this study was to create a novel integrated multi-criteria decision-making (MCDM) model for the selection of pavers for the middle category of roads. A total of 16 criteria were defined and then divided into four main groups, on the basis of which the performance of 12 pavers was evaluated. Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA) with D numbers (IMF D-SWARA) was extended to determine the significance of the criteria for the selection of construction machinery based on two groups of experts. Rough measurement of choices and their ranking as a compromise solution (R-MARCOS) was used to evaluate and rank the performance of construction machinery. The results show that three alternatives out of the set considered can satisfy defined requirements. After that, we performed a multi-phase validity test in which different values of criterion weights were simulated. A comparative analysis with seven other Rough MCDM methods was also created, and the Spearman’s correlation coefficient (SCC) and WS coefficient were calculated to determine the correlation of ranks for sensitivity analysis and comparative analysis. Thus, the obtained results were verified.

The construction industry, as one of the most complex sectors, depends on using wasted and recycled materials, timely decision-making, and adequate execution of all activities in supply chains. This paper presents tests of mixtures for cold in-place recycling where existing material is used. In this research, we used cement and bitumen emulsion as well as fly ash, zeolite, slag, and Bakelite. A total of seven mixtures were tested in order to increase sustainability. It was tested the indirect tensile strength and dynamic modulus of elasticity after seven and 28 days for dry specimens, after 28 days for water-saturated specimens and for specimens exposed to frost. After completing the tests using the MEREC (MEthod based on the Removal Effects of Criteria) and CoCoSo (Combined Compromise Solution) multi-criteria model, mixtures were evaluated and ranked in terms of mechanical properties, price, and environmental protection. Considering the ranking of mixtures using the CoCoSo method, the highest quality mixtures, for most combinations of weight factors, are mixtures with slag, mixtures with fly ash, and mixtures with 2% of cement and 2% of bitumen emulsion. Sensitivity analysis was also performed with new simulated values of the criteria in order to determine the individual influence of the criteria on the ranking of mixtures. The conclusions are as follows: the use of bitumen emulsion, cement, waste materials, and other materials in cold recycling would reduce the cost of recycling pavement structures, increase environmental protection, while the mechanical properties of the pavement structures are within acceptable limits.

One of the most important challenges when building road infrastructure is the selection of appropriate mechanization, on which the efficiency of construction and the life of exploitation depends largely. As construction machinery, pavers occupy a significant place in civil engineering projects, so their selection, depending on a road category, is a very important activity. The objective of this paper is to develop an intelligent Fuzzy MCDM (Multi-Criteria Decision-Making) model, which consists of the integration of D and Z numbers for the selection of construction machinery. The IMF D-SWARA (Improved Fuzzy D Step-Wise Weight Assessment Ratio Analysis) method was used to determine weighting coefficients. A novel Fuzzy ARAS-Z (Additive Ratio Assessment) method has been developed to determine an adequate paver for a lower category of roads (asphalt width up to 5 m), which represents an important contribution and novelty of the paper. A total of 10 alternatives were evaluated based on 16 criteria which were classified into 4 main groups. The results have shown that the alternative A8—SUPER 1300-3 represents a paver with the best characteristics for the considered set of parameters. After that, verification tests were calculated, and they include a comparative analysis with four other MCDM methods based on Z numbers, a change in the normalization procedure, and the impact of changing the size of an initial fuzzy matrix. The tests showed the stability of the developed model with negligible deviations.

Asphalt production plants play an important role in the field of civil engineering, but also in the entire economic system since the construction of roads enables uninterrupted functioning within it. In this paper, the ranking of asphalt production plants on the territory of the Autonomous Province of Vojvodina has been performed. The modern economy needs contemporary models and methods to solve complicated MCDM problems and, for these purposes, it has been developed an original Interval Rough Number (IRN) Multi-criteria decision-making (MCDM) model that implies an extension of two methods belonging to the field with interval rough numbers. After forming a list of eight most significant criteria for assessing the efficiency of asphalt production plants, the Interval Rough Number PIvot Pairwise RElative Criteria Importance Assessment (IRN PIPRECIA) method was developed to determine the significance of the criteria. A total of 21 locations with asphalt mixture installation were considered. For that purpose, seven asphalt production plants were included, and for their ranking, the IRN EDAS (Evaluation based on Distance from Average Solution) method was created. The aim of this paper is to develop a novel interval rough model that can be useful for determining the efficiency of asphalt production plants. Averaging in group decision-making (GDM) for both methods was performed using an IRN Dombi weighted geometric averaging (IRNDWGA) aggregator. The obtained results show that (A15) Ruma (SP)–Mačvanska Mitrovica–Zasavica has the best characteristics out of the set of locations considered in this study. However, Alternatives A6 and A19 are also variants with remarkably good characteristics since there is very little difference in values compared to the first-ranked alternative. Also, the obtained results have shown that the developed model is applicable, which is proven through a comparative analysis.

The planning of road infrastructure undergoes major changes, especially in terms of sustainable development. Recycling of pavement structures involves the reuse of materials from existing pavement structures due to its timesaving and environmental benefits, as well as cost reduction. According to the recycling temperature, recycling can be hot and cold. This paper deals with cold in-place recycling and the determination of the optimum fluid content for by-product materials in mixtures compared with one containing natural zeolite. The content of bitumen emulsion and cement—which are the most used materials so far in cold recycling along with foam bitumen—was replaced with fly ash, slag or natural zeolite, and bakelite, respectively, while recycled asphalt pavement from Serbia (Žabalj) was used. Six different mixtures were made. The mixture with the addition of fly ash had the highest optimum fluid content (7.6%) compared with all test mixtures. Mixtures with slag, natural zeolite, and bakelite were in the range of a mixture containing 2% cement. Furthermore, the mixture with 3% cement had the lowest optimum fluid content (5.7%) in comparison to all the mixtures that were tested.