The transport is an important part of logistic systems. Improper management of transport operations may contribute to the low level of the usage of vehicles and to high transport costs, as well as to the formation of unnecessary high inventory at each location of storage, as well as prolonged time of order realization and not full use of company capacity. It is therefore important the appropriate dimensioning, planning of the transport system and performed transport operations so as to allow the supply of certain goods at the right time and the amount to the appropriate points of the system. The article presents the methods of transport operations modelling, taking into account different criteria based on discrete event simulation. In the article the case study of modelling transport operations in the small cross-docking centre is also presented

The article presents one of the most commonly used approaches to management, namely process approach and process manage - ment. This problem is quite complex due to the number of processes carried out by hard coal mining enterprises. The classification of processes according to three categories such as: management processes, core processes and supporting processes is discussed. Attention is paid to the efficiency and effectiveness of the process and the measures used to manage these processes. The cognitive goal of this article was to gain knowledge about the use of process management in hard coal mining enterprises. The aspects selected by the authors concerned the analysis of the processes carried out by these enterprises. In particular, the process of Occupational Health and Safety (OHS) Management and “Environmental Protection” (EP) has been analyzed. Their input and output elements are presented, as well as exemplary measures of their effectiveness.

A sandwich pallet loading problem represents a significant challenge in the logistics of fast-moving consumer goods (FMCG), requiring optimisation of load units (LUs) arrangements to minimise their number in transportation and warehousing processes, leading to an environmental responsibility of organisations. This study introduces an innovative approach combining Dominance-Based Rough Set Theory (DRST) with a rule-based expert system to improve the efficiency of the pallet loading and to provide sustainable development. Key criteria and attributes for the LU assessment, such as weight, height, and fragility, are defined. DRST is utilised to classify these units, leveraging its capability to handle imprecise and vague information. The rule-based system ensures an optimal arrangement of LUs by considering critical control parameters, thereby reducing LU numbers and mitigating the environmental impact of logistics operations, as measured by energy consumption. The proposed approach is validated using real-world data from the FMCG distribution company. Results demonstrate that integrating DRST with an expert system improves decision-making consistency and significantly reduces the number of LUs. This study shows a way to increase the level of environmental responsibility of the organisation by cutting energy consumption and delivering economic and social benefits through fewer shipments. For example, the approach reduces energy consumption for a customer order delivery by 40%, from 0.60 to 0.36 (kWh/pskm).

Planning the operation of urban public transport vehicles is the first stage of operational planning and consists in combining timetable tips, which are input data, into blocks that constitute the daily tasks of vehicles. For a large mixed fleet of vehicles of various types, especially those with battery power that requires recharging, operating from many depots, with numerous requirements and rolling stock constraints, the problem is a major engineering challenge, even for an experienced team of planners. IT solutions based on realistic, mathematical decision-making models and fast optimization algorithms can be of great assistance. For the problem formulated this way, a mathematical decision model with a multi-criteria objective function was built, taking into account technical, economic, and ecological criteria, natural, and binary decision variables. The model takes into account the real requirements and constraints, a mixed fleet of different types vehicles, including electric buses, multiple depots, technical trips (dead heads), and battery charging. The considered problem is an NP-hard combinatorial optimization problem. The use of classical, exact algorithms to solve this problem is not possible for schedules with many thousands of line trips and fleets of hundreds or thousands of vehicles. This research proposes an original, dedicated heuristic, enabling to obtain an acceptable, but still suboptimal solution, in a very short time. The tests of the proposed heuristic algorithm were carried out on real databases of public transport systems of the two selected medium and large Polish cities. In particular, multiple depots, a mixed fleet of different types of vehicles, and real-world constraints were taken into account. The results of computer experiments carried out using the developed heuristic were compared with the results obtained manually by a team of experienced and expert planners. For the developed multi-criteria decision-making model results comparable to and better than those prepared manually by experts were obtained in a very short time using the proposed heuristics. It is the basis for further development works on expanding the model and improving the optimization algorithm.