1,721,000 research outputs found
Metodologie matematiche per l'analisi dell'efficienza del trasporto collettivo urbano ed interurbano
No full textA Benders decomposition algorithm for demand-driven metro scheduling
Full text linkMetro timetables are usually planned with a top-down approach. After dividing the day into different periods, the trains are scheduled between the terminals of the line with a fixed frequency per period. In this paper we adopt an alternative paradigm where trains are scheduled individually. The schedule is developed so as to best match the passenger demand, and trains may short-turn at intermediate stations, thus reversing their direction before reaching the line terminal. This type of approach is particularly suited for automated metro lines, since it has a limited impact on personnel management. Considering the objective of minimizing the passenger waiting times on a two-directional metro corridor, we make two operating assumptions when designing the train schedule. Specifically, we assume the presence of a root station, which cannot be skipped by short-turning, and we assume that idling is only allowed immediately after a short-turn, and for a maximum amount of time. We present a path-based formulation for the problem and develop an efficient exact algorithm for it using a Benders-based branch-and-cut algorithm. We evaluate the proposed formulation and algorithm on a number of test instances. Through our computational experiments, we demonstrate the effectiveness of the developed formulation and algorithm
Soil is brown gold in the Emilia-Romagna region, Italy
No full textSoil is a natural resource essential to human welfare by virtue of its numerous crucial functions. In the past, soil has been taken for granted because of its widespread, albeit finite, availability. However, now that world's population is projected to exceed ten billion before the end of this century, soil is increasingly perceived as a precious commodity. Consequently, soil is increasingly under pressure by rich private investors and governments within the poorest countries to satisfy appetites for food production and biofuel. A case study is used to explore the plausibility of soil being considered as ‘brown gold’. Based on the comparison of land use maps, we estimated the value in terms of resource from raw material, carbon sink and virtual calories of the productive soil lost during the period 2003–2008 in the Emilia-Romagna Plain, one of the most productive areas of Italy. More than fifteen thousand hectares of cropland underwent land use change – in particular urbanization – over the 6-year period with an implied loss of crop production potential equivalent to the daily calorific requirement of more than 440,000 people. Taking into account that Italy is no longer self-sufficient in food production, such a loss appears to be strategically significant. Perhaps more importantly, urbanization and soil sealing has had negative ramifications on environmental sustainability, on both local and broad scales, with increased consumption of public funds. A logical framework of the socio-economic impact of land use change has been compiled and is presented as a possible example of a policy relevant approach to managing productive soils as a finite resourc
Demand-Driven Timetabling for a Metro Corridor Using a Short-Turning Acceleration Strategy
Full text linkThe efficient management of metro lines is a major concern for public transport operators. Traditionally, metro lines are operated through regular timetables, that is, timetables where trains have a constant headway between all stations. In this paper, we propose a demand-driven metro timetabling strategy and elaborate exact solution methods for the case of a two-directional metro corridor. In doing so, we avoid imposing any predetermined structure to the timetable, and instead control the trains individually to best match passenger demand. We consider that trains may short turn, that is, trains that are not required to serve the line from terminal to terminal, but instead may reverse direction before reaching the terminal. We present a mixed integer linear programming formulation for the demand-driven timetabling problem of a two-directional metro corridor with short turning. Furthermore, we develop an efficient exact algorithm using cut generation for an alternative formulation with an exponential number of constraints, and derive two classes of valid inequalities. We evaluate the proposed formulation and algorithm considering seven possible cut generation strategies on a number of test instances from artificially generated lines and on two test beds derived from real-world lines. Through the computational experiments, we demonstrate the effectiveness of the developed algorithm and the added value of the proposed strategy in terms of passengers' waiting time
A modeling framework for the passenger assignment on a transport network with time-tables
No full textA personalized walking bus service requiring optimized route decisions: A real case
Full text linkWe address the design of the lines of a Walking Bus service according to a new paradigm, where children are picked up at home. The scarcity of accompanying persons together with the limit on the length of the deviations from the shortest itinerary of each child make the problem different from the traditional school bus and walking bus design. We propose an arc-based model, a path-based model tackled by column generation, and a heuristic procedure. Solution approaches are tested on a set of real and realistic instances. Real instances refer to the case study of a primary school in Italy
Carbon stocks in peri-urban areas: a case study of remote sensing capabilities
Full text linkPeri-urban areas are the extension of cities into contiguous areas, where households and farms coexist. Carbon stocks (CSs) assessment, a concept here extended to urban features, has not yet been studied in depth over peri-urban areas due to uncertainties in such CSs quantification, level of detail required about construction materials, and the high spatial variability of those stocks. Remote sensing (RS)-based techniques have been successfully utilized in urban areas for assessing phenomena such as soil sealing, sprawl patterns, and dynamics of surface imperviousness, especially focusing on land cover classification at high to medium spatial scales. Over the floodplain study area of Emilia-Romagna region (Italy), we compared mapping products derived from Landsat multiseasonal data with different CSs, in soils and impervious surfaces, such as buildings and roads. A multiscale correlation analysis and regression assessment between CSs layers and satellite products were run at different grid cell sizes (100, 250, 500, and 1000 m). Results show that RS products from processing of mid-resolution satellite data can effectively perform well enough to estimate CSs in peri-urban areas, especially at 500–1000 m scale. Urban Fraction Cover method, derived through weighting urban land cover classes (including dense, sparse, and industrial urban features) can represent a good proxy of the ratio of anthropogenic over natural CSs (R2 up to 0.75). Imperviousness Index (II) product scored high positive correlation with CSs over built-up areas (R2 up to 0.77), and strong negative correlation with organic carbon density in soil (R2 up to 0.73
The balanced p-median problem with unitary demand
No full textWe consider a bi-objective variant of the -median problem where facilities must be located to serve a set of customers with unitary demand. The considered objectives are: minimizing the average traveled distance between customers and facilities, and balancing the number of allocated customers per facility. We denote the latter by customer allocation inequity and measure it as the mean absolute deviation of the number of customers assigned to each median. We formulate this new problem as a bi-objective mixed-integer linear program ,and use a weighted sum method to generate a representative set of Pareto optimal solutions. Considering the single-objective subproblem solved by the weighted sum method, we develop a primal–dual algorithm that handles large-scale instances by combining a Lagrangian relaxation heuristic within a variable neighborhood search metaheuristic. This algorithm relies on the solution of a tailored minimum cost flow problem for the case where the locations of the facilities are known. We evaluate the proposed formulation and algorithm on test instances from the literature. After demonstrating the effectiveness of the developed algorithm, we test it on a series of large instances derived from an industrial application of districting for last-mile delivery. We analyze the trade-off between the assignment cost and customer allocation inequity, and evaluate the quality of the solutions by comparing them with those attained through alternative inequity measures
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