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EN
The article presents the original, mixed method of determining the range of individual settlement units within the existing administrative areas. Using GIS tools and raster graphics processing programs, it is possible to delimit urbanised clusters also in rural areas, for which no separate statistical and spatial data is collected. Additionally, thanks to the application of the presented method, it is possible – in some cases, to indicate the centrality of a given settlement unit, even in the absence of a spatially crystallised place, such as a square or main public park. The tool can be used on a subregional and local scale both to identify compact building structures in order to value them in terms of spatial order and to study their potential for transport-oriented development.
PL
W artykule przedstawiono autorską mieszaną metodę wyznaczania zasięgu poszczególnych jednostek osadniczych w obrębie istniejących obszarów administracyjnych. Wykorzystując narzędzia GIS i programy z zakresu grafiki wektorowej i rastrowej, możliwe jest wyodrębnienie skupisk obszarów zurbanizowanych także na obszarach wiejskich, dla których nie są gromadzone odrębne dane statystyczne i przestrzenne. Dodatkowo dzięki zastosowaniu prezentowanej metody możliwe jest wskazanie zwartych zespołów zabudowy w celu identyfikacji ich jakości w zakresie ładu przestrzennego, jak i do określenia ich potencjału dla rozwoju zorientowanego na transport. Narzędzie może być stosowane w skali subregionalnej i lokalnej.
EN
Scheduling buses in public transport systems consists in assigning trips to vehicle blocks. To minimize the cost of fuel and environmental impact of public transport, the number of vehicle blocks used should be as small as possible, but sufficient to cover all trips in a timetable. However, when solving real life transportation problems, it is difficult to decide whether the number of vehicle blocks obtained from an algorithm is minimal, unless the actual minimal number is already known, which is rare, or the theoretical lower bound on the number of vehicles has been determined. The lower bound on the number of vehicle blocks is even more important and useful since it can be used both as a parameter that controls the optimization process and as the minimum expected value of the respective optimization criterion. Therefore, methods for determining the lower bound in transportation optimization problems have been studied for decades. However, the existing methods for determining the lower bound on the number of vehicle blocks are very limited and do not take multiple depots or heterogeneous fleet of vehicles into account. In this research, we propose a new practical and effective method to assess the lower bound on the number of vehicle blocks in the Multi-Depot Vehicle Scheduling Problem (MDVSP) with a mixed fleet covering electric vehicles (MDVSP-EV). The considered MDVSP-EV reflects a problem of public transport planning encountered in medium-sized cities. The experimental results obtained for a real public transport system show the great potential of the proposed method in determining the fairly strong lower bound on the number of vehicle blocks. The method can generate an estimated distribution of the number of blocks during the day, which may be helpful, for example, in planning duties and crew scheduling. An important advantage of the proposed method is its low calculation time, which is very important when solving real life transportation problems.
EN
This paper presents the problem of public transport planning in terms of the optimal use of the available fleet of vehicles and reductions in operational costs and environmental impact. The research takes into account the large fleet of vehicles of various types that are typically found in large cities, including the increasingly widely used electric buses, many depots, and numerous limitations of urban public transport. The mathematical multi-criteria mathematical model formulated in this work considers many important criteria, including technical, economic, and environmental criteria. The preliminary results of the Mixed Integer Linear Programming solver for the proposed model on both theoretical data and real data from urban public transport show the possibility of the practical application of this solver to the transport problems of medium-sized cities with up to two depots, a heterogeneous fleet of vehicles, and up to about 1500 daily timetable trips. Further research directions have been formulated with regard to larger transport systems and new dedicated heuristic algorithms.
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