Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has great importance for energy generating capacity scheduling and power system management. This paper presents a review of forecasting methods and models for electricity load. About 45 academic papers have been used for the comparison based on specified criteria such as time frame, inputs, outputs, the scale of the project, and value. The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting. As for short-term predictions, machine learning or artificial intelligence-based models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Fuzzy logic are favored.

Traffic air pollution significantly influences cyclists using cycling routes near main roads. We analyze the dependency of black carbon (BC) concentrations in relation to the proximity to their traffic sources. We performed static and mobile measurements of BC using aethalometers at chosen sites and cycling routes in Celje, Slovenia—static measurements at two road-side sites and an urban background site. Mobile measurements were performed simultaneously at an existing cycling route and an alternative route away from the busy roads. BC concentration apportioned to traffic decreases with the distance from the sources on the main road. The exposure of cyclists to BC can be greatly reduced by moving the cycling route away from busy roads, hence we propose an alternative route and show that traffic planning and management should include all modes of transport. Results imply that street intersections along the cycling routes influence the cyclists’ exposure and should be as few as possible when planning cycling routes in urban areas.

Sustainable engineering is very important for logistics systems. Nowadays, sustainable warehouse management is a key factor in market success. Workforce fluctuation and inverting the number of customers’ demands make a lot of problems in distribution warehouses. This study addresses a sustainable approach for the workforce scheduling problem recognized in a real distribution warehouse. The problem arises from the high variability of demand for workers over one workday, which causes workforce surplus in some periods of the workday and shortages in others. Engineering managers of the distribution warehouse already use different full-time and part-time shifts, and schedule workers on different activities, but they still have significant workforce surpluses or shortages in some periods. This study proposes the scheduling of activities’ execution together with workers to face that variability and decrease the cost of the workforce. This idea comes from the fact that some activities in a distribution warehouse can be done in a specific time period after the need for them occurs. In this way, the variability of demand for workers can be decreased, and a lower workforce cost may be ensured. Based on this idea, the entire problem is modeled as integer linear programming. The real example of the problem is solved, and the proposed model is tested on randomly generated instances of the problem in Python by means of the PuLP linear programming package. The results indicate different positive effects in the manner of sustainable warehouse management: lower workforce costs, time savings, better utilization of all types of resources and equipment, increased employee satisfaction, and so on. For even 61% of instances of the introduced problem, the obtained cost of the workforce is lower by more than 20% if activities’ executions are scheduled together with employees.

The manuscript discusses the investigation of vehicle flow in a predesignated junction by an appropriate traffic flow management with an effort to minimize fuel consumption, the production of CO₂, an essential greenhouse gas (hereinafter referred to as GHG), and related transport costs. The particular research study was undertaken in a frequented junction in the city of Celje, located in the eastern part of Slovenia. The results obtained summarize data on consumed fuel and produced CO₂ amounts depending on the type of vehicle, traffic flow mixture, traffic light signal plan, and actual vehicle velocity. These values were calculated separately for three different conditions of traffic flow management. Amounts of fuel consumed were experimentally investigated in real traffic situations, whereas CO₂ production was calculated by applying the actual European standard entitled EN 16258:2012 associated with a guideline for measuring emission values, as well as by examining specific traffic flow parameters. The key objective of the manuscript is to present multiple scenarios towards striving to minimize environmental impacts and improve transport operation’s economic consequences when implementing proper traffic flow management. As for crucial findings, we quantified fuel consumption and CO₂ emissions based on real data on the number and type of vehicles crossing the examined intersection and traffic light switching intervals. The results show that most of the CO₂ was produced while waiting and in the accelerating phase in front of traffic lights, whereby in the running phase through the intersection, significantly less fuel was used. This study represents a mosaic fragment of research addressing endeavors to reduce CO₂ production in urban transport. Following the experiments conducted, we can see a notable contribution towards reducing CO₂ production with known and tested interventions in the existing transport infrastructure. A procedure embracing individual research steps may be deemed as an approach methodology dealing with traffic flow management with an aim to decrease the environmental and economic impacts of traffic and transport operation; this is where the novelty of the research lies.

Supply chain disruptions and challenges have and will always exist, but preparing in advance and improving resilience for the upcoming consequences should be the utmost important goal. This paper explores trends that affect innovation in the technological sphere of supply chain systems. More precisely, the research is focused on Digital Twin technology applicability through other logistics IT trends and aims to research the pressing issue of ensuring the visibility and resilience of future supply chain systems. The paper’s objective is to produce a conceptual model enabling the investment assessment of the necessary IT resources. Initially, a theoretical confirmation of logistics IT trends’ relevance to supply chain systems was established. After, propositions of Digital Twin technology applications to other logistics IT trends were made, which were divided into corresponding constant multitudes of supply chain systems. Lastly, the conceptual model for the investment assessment of the necessary IT resources was derived in the form of a matrix. It considers 16 parameters for investment assessment and applicability to all companies, regardless of their specifics. It also supports the notion of digital IT competencies’ fundamental importance to the continuous operation of supply chain systems.

Today, sharing knowledge requires taking into account many aspects. Variable environmental conditions, the people factor, and the security of resources are just a few that should be considered for a noticeable improvement in the functioning of the company. Supporting this course of action requires the identification of all barriers that may exist in the enterprise. Only the owner and senior management by establishing system and organizational changes can influence this element of the business. The aim of the article is to indicate the problems in this respect that block the proper functioning of the company in the field of information and knowledge exchange. The survey was conducted with the help of a questionnaire among 189 respondents. The industry has significantly decreased in the last few decades, currently there are 307 companies operating in Poland. Conclusions from the conducted research were collected on the basis of a questionnaire survey. The further stage of the research will be to compare the collected results with the results from Western European countries.