Solving real-life problems using multi-criteria decision-making methods is now an everyday challenge. These methods represent a very useful tool and support for decision-making in all areas. Therefore, this paper comprises evaluation and selection of the PVC carpentry manufacturers using a combined multi-criteria model. Five potential manufacturers are evaluated on the basis of seven criteria. For the determination of criteria weights, the FUCOM (FUll COnsistency Method) is used, while the Multi-Attributive Border Approximation Area Comparison (MABAC) method is used for evaluating and selecting the PVC manufacturer. The results show that the third alternative is the most suitable solution, as demonstrated by the sensitivity analysis. Four other methods are used in the sensitivity analysis, namely, ARAS (Additive Ratio Assessment), WASPAS (Weighted Aggregated Sum Product Assessment), EDAS (Evaluation based on Distance from Average Solution), and SAW (Simple Additive Weighting). The obtained results using all the methods show the complete correlation of the ranks obtained using the MABAC method.

Material Handling Equipment is a set of different tools, devices, applications that aim to facilitate the handling of materials and products. It is used inside the warehouse, but also between warehouses and production facilities. As an important type of material handling equipment, automatically guided vehicles (AGVs) play one of the key roles in warehouse automation. The benefits of applying the AGVs in the warehouse automation process include: reducing labor costs, increasing reliability and productivity, reducing the damage of goods, safety improving, managing and controlling the complete system, etc. In this paper, a Novel Rough Range of Value Method (R-ROV) for evaluating and selecting AGVs in the warehouse has been developed, which is one of the main contributions. In addition, the Full Consistency Method (FUCOM) was used to determine the weight values of the criteria. The model was formed through nine AGVs and 7 criteria. In the framework of checking the stability of the obtained results and the developed model, the comparison was performed using: Rough WASPAS (Weighted Aggregated Sum Product ASsessment), Rough SAW (Simple Additive Weighting) and Rough MABAC (Multi-Attributive Border Approximation area Comparison). Sensitivity analysis showed high correlation of ranks with all the applied methods by employing the Spearman's Correlation Coefficient (SCC).

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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.

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