Energy is vital for the proper functioning of the various sectors of the economy and social life. During the pandemic, there have been some changes in these aspects that need to be investigated. The main objective of this article is to identify the direction of change caused by the COVID-19 pandemic in energy consumption and energy intensity in sectors and economic areas in EU countries. The specific objectives are to identify the importance of energy consumption in sectors and areas of the economy in individual EU countries; to determine the dynamics of change and variability during the pandemic in energy consumption in individual sectors and areas of the economy in EU countries, especially during the COVID-19 pandemic; to determine the changes in energy intensity of individual economic sectors and the differences in energy intensity between individual EU countries, including during the COVID-19 pandemic. Using a purposive selection method, all 27 EU Member States were selected for the study on 31 December 2020. The analysed period covered the years 2005–2020. The sources of material were literature and data from Eurostat. Descriptive, tabular and graphical methods, dynamic indicators with a fixed base and variable base, Gini coefficient, coefficient of variation, Pearson’s linear correlation coefficient, and multi-criteria analysis were used for analysis and presentation. It was found that the structure of energy consumption had remained unchanged for several years, with transport, industry and households dominating. There were no significant differences between countries. The COVID-19 pandemic reduced energy consumption in all sectors of the economy, the largest in transport and services and the smaller in industry. At the same time, household energy consumption increased. As a result of the pandemic, there was an increase in energy intensity in all sectors of the economy, the largest in industry. Western European countries had a lower energy intensity of the economy than Central and Eastern European countries. There was little change over several years. Countries generally maintained their ranking. The pandemic did not change anything in this respect, meaning that it had a similar impact on individual EU countries.

The rapid growth in the volume of international container transport requires that the entire transport chain become more competitive, including maritime container terminals. The aim of the article is to identify the number and location of major Baltic container terminals and to perform a multi‑criteria analysis of the competitiveness of maritime container terminals in the Baltic Sea Region (BSR). In our study, we perform the AHP multi‑criteria analysis with subjective criteria weights, as well as the entropy method with objective criteria weights. Thus, we can evaluate the competitive advantages of each of the specified terminals in the region. We are among the first to study the competitiveness of individual maritime container terminals in the BSR. Thus, our research adds to the literature that has yielded results on the competitive advantage of the Baltic seaports.

W pracy Optymalizacja w logistyce. Modelowanie logistycznych procesów decyzyjnych (Iwona Konarzewska, Maciej Jewczak, Adam Kucharski, red. nauk. Iwona Konarzewska, Łódź 2020) przedstawiono podstawowe sposoby modelowania zagadnień logistycznych za pomocą wzorów programowania liniowego, przydziału oraz innych metod z zakresu badań operacyjnych. Omówiono także zagadnienia związane z planowaniem sieciowym, zarządzaniem projektami, modelowaniem zagadnień masowej obsługi i prognozowaniem popytu. Książka Optymalizacja w logistyce. Modelowanie przepływów w kanałach dystrybucji kontynuuje postawione zadanie poszukiwania optymalnych rozwiązań w problemach logistycznych. Adresowana jest zarówno do logistyków, rozwiązujących w praktyce problemy zasygnalizowane w pracy w licznych przykładach, jak i do studentów logistyki, zarządzania oraz informatyki, pragnących poznać tajniki metod optymalizacyjnych stosowanych w zagadnieniach logistycznych. Autorzy wzięli pod uwagę: zadania lokalizacji centrów dystrybucyjnych, szeroko rozumiane problemy transportowe i algorytmy ich rozwiązywania, problemy układania tras oraz optymalizacji w sieciach transportowych (w tym wyznaczania maksymalnego, a także najtańszego przepływu w sieci). Omówione zostały również sposoby klasyfikacji i analizy zapotrzebowania na produkty, a także modele wspomagające tworzenie strategii uzupełniania zapasów (wielkość dostawy, ustalanie momentu wykonania zamówienia). W publikacji przedstawiono algorytmy harmonogramowania zadań produkcyjnych i modelowania przepływów produkcyjnych oraz, w sposób syntetyczny, podstawowe metody modelowania symulacyjnego – metodę dynamiki systemów, symulacji zdarzeń dyskretnych, modelowania wieloagentowego.