When selecting a building material supplier, contractors may take into consideration a large number of criteria that are often subjective and hard to measure. Including them all in the evaluation may be beneficial, yet in practice it may generate many complications. A solution is provided by one of the multicriteria analysis methods. The article describes the criteria employed in the evaluation of building material suppliers. One multicriteria analysis method, namely the analytic hierarchical process (AHP), is argued to be a useful alternative. An example of its application involving its basic and the more sophisticated variant, the fuzzy analytic hierarchical process (FAHP) with extent analysis method, is presented. As the results reveal, real decisive problems require methods resembling human reasoning, which is often characterized by uncertainty and subjectivity of evaluation. The real problem presented in the paper proves that the FAHP method may have a practical application.

This paper proposes the author’s model based on the Fuzzy Analytic Hierarchy Process (FAHP) to improve the efficiency of contractor bidding decisions. The essence of the AHP method is to make pairwise comparisons of available options against all evaluation criteria. The results of these comparisons are recorded in a square matrix in which symmetrical elements are reciprocal. In the expert opinion, a 9-step, bipolar verbal scale was used so that the symmetry of the response was maintained. For contractors from countries where the tendering system is commonly used, the choice of the right tender in which to participate influences their image, financial condition, and their aspiration to succeed. The bid/no bid decision depends on numerous factors associated with the company itself, the environment, and the project concerning the tender. When facing tough competition, contractors search for a solution which increases their chances of winning the tender. The proposed model was based on factors selected by Polish contractors. The original element of the model involves 4 original criteria and 15 sub-criteria for the assessment of investment decision projects to the selection of the most advantageous contract, i.e., the contractor’s participation in the bid. For verbal evaluations describing the criteria, symmetric triangular fuzzy numbers were assigned. The authors performed an extended analysis method combined with FAHP in the model. Fuzzy evaluations underwent elaborate analysis, the aim of which was to specify the synthetic priority weights for each criterion. As a result of the application of the method, to prove that the model works, an example from the Polish construction market was presented in which a bid/no bid decision about four possible tenders was to be taken. Despite the considered example applying to Polish conditions, the proposed model can be used also in other countries. The authors’ rationale is to produce new and more flexible methodologies in order to realistically model a variety of concrete decision problems.

Efficiently functioning public transport has a significant positive impact on the entire transportation system performance through numerous aspects, such as the reduction of congestion, energy consumption, and emissions. In most cases, the basic elements of public transport are the bus transport subsystem. Currently, in addition to criteria such as punctuality, the frequency of departures, and the number of transfers, a travelling comfort level is an important element for passengers. An overcrowded bus may discourage travelers from choosing this mode of transport and induce them to use a private car despite the existence of many other facilities offered by a given public transport system. Therefore, the forecasting of bus passenger demand, as well as bus occupancy at individual bus stops, is currently an important research direction. The main goal of the article is to present the conceptual framework for the Advanced Travel Information System with the prediction module. The proposed approach assumes that the prediction module is based on the use of the Markov Chain concept. The efficiency and accuracy of the obtained prediction were presented based on a real-life example, where the measurements of passengers boarding and alighting at bus stops were made in a selected Cracow bus line. The methodology presented in the paper and the obtained results can significantly contribute to the development of solutions and systems for a better management as well as a cost and energy consumption optimisation in the public transport system. Current and forecasted information related to bus occupancy, when properly used in the travel information system, may have a positive impact on the development of urban mobility patterns by encouraging the use of public transport. This article addresses the current and practical research problem using an adequate theoretical mathematical tool to describe it, reflecting the characteristics and nature of the phenomenon being studied. To the best of the authors’ knowledge, the article deals for the first time with the problem of prediction of onboard bus comfort levels based on in-vehicle occupancy.

Energy costs account for a significant proportion of total costs in production systems. Since energy is becoming an increasingly expensive resource, therefore, it is critical to consume it as efficiently as possible. Focusing on energy efficiency is also important in terms of reducing greenhouse gas (GHG) emissions and the effects of other pollutants on the environment. One of the possible ways for businesses to reduce energy consumption is to use available transportation means as efficiently as possible. In the operational phase, this can be achieved by reducing unnecessary transport, selecting the most efficient delivery routes, and by optimized assignment of available vehicles to transportation orders. We present in this article a novel dynamic assignment of transportation orders to fleet with energy minimization criterion in internal transport system of a printing company. The novelty of the proposed model is that, in contrast to most existing models, it can handle a heterogeneous fleet of human-operated and autonomous mobile robots (AMRs). The minimization of the energy consumption by transportation vehicles was modeled with reference to VDI 2198 standard. The need for such a model is justified by the fact that it better reflects a real production environment in many companies. The proposed optimization model was tested in simulation experiments imitating real production conditions in a large web printing house. The obtained results show that the proposed model allows for a significant reduction of energy consumption in internal transportation. The proposed model is general enough to be used in various companies with a heterogeneous fleet of internal transportation vehicles. In addition, the energy consumption factor VDI for AMRs has been determined, which can be useful in solving various problems related to energy optimization of internal transportation.

This article examines the influence of specific time series attributes on the efficacy of fuel demand forecasting. By utilising autoregressive models and Markov chains, the research aims to determine the impact of these attributes on the effectiveness of specific models. The study also proposes modifications to these models to enhance their performance in the context of the fuel industry’s unique fuel distribution. The research involves a comprehensive analysis, including identifying the impact of volatility, seasonality, trends, and sudden shocks within time series data on the suitability and accuracy of forecasting methods. The paper utilises ARIMA, SARIMA, and Markov chain models to assess their ability to integrate diverse time series features, improve forecast precision, and facilitate strategic logistical planning. The findings suggest that recognising and leveraging these time series characteristics can significantly enhance the management of fuel supplies, leading to reduced operational costs and environmental impacts.