Optimal Alignments for Designing Urban Transport Systems: Application to Seville

The achievement of some of the Sustainable Development Goals (SDGs) from the recent 2030 Agenda for Sustainable Development has drawn the attention of many countries towards urban transport networks. Mathematical modeling constitutes an analytical tool for the formal description of a transportation system whereby it facilitates the introduction of variables and the definition of objectives to be optimized. One of the stages of the methodology followed in the design of urban transit systems starts with the determination of corridors to optimize the population covered by the system whilst taking into account the mobility patterns of potential users and the time saved when the public network is used instead of private means of transport. Since the capture of users occurs at stations, it seems reasonable to consider an extensive and homogeneous set of candidate sites evaluated according to the parameters considered (such as pedestrian population captured and destination preferences) and to select subsets of stations so that alignments can take place. The application of optimization procedures that decide the sequence of nodes composing the alignment can produce zigzagging corridors, which are less appropriate for the design of a single line. The main aim of this work is to include a new criterion to avoid the zigzag effect when the alignment is about to be determined. For this purpose, a curvature concept for polygonal lines is introduced, and its performance is analyzed when criteria of maximizing coverage and minimizing curvature are combined in the same design algorithm. The results show the application of the mathematical model presented for a real case in the city of Seville in Spain.Ministerio de Economía y Competitividad MTM2015-67706-

GRASP algorithms for the robust railway network design problem

This paper analyzes the solvability of a railway network design problem and its robust version. These problems are modeled as integer linear programming problems with binary variables, and their solutions provide topological railway networks maximizing the trip coverage in the presence of a competing mode, both assuming that the network works fine and that links can fail, respectively. Since these problems are computationally intractable for realistic sizes, GRASP heuristics are proposed for finding good feasible solutions. The results obtained in a computational experience indicate that our GRASP algorithms are suitable for railway network design problems. © 2011 Springer Science+Business Media, LLC.We would like to thank the Spanish Ministerio de Fomento under grant PT-2007-003, Ministerio de Ciencia y Educacion under grant MTM2009-14243, the Junta de Andalucia under grant P09-TEP-5022 for supporting this research, the FEDER funds of the European Union and TUSSAM (Seville, Spain). Special thanks are due to two anonymous referees for their valuable comments.García-Archilla, B.; Lozano, AJ.; Mesa, JA.; Perea Rojas Marcos, F. (2011). GRASP algorithms for the robust railway network design problem. Journal of Heuristics. 19(2):399-422. https://doi.org/10.1007/s10732-011-9185-zS399422192Baaj, M., Mahmassani, H.: An AI-based approach for transit route system planning and design. J. Adv. Transp. 25(2), 187–210 (1991)Cancela, H., Robledo, F., Rubino, G.: A grasp algorithm with tree based local search for designing a survivable wide area network backbone. J. Comput. Sci. Technol. 4(1), 52–58 (2004)Díaz, J.A., Luna, D., Luna, R.: A grasp heuristic for the manufacturing cell formation problem. TOP (2011). doi: 10.1007/s11750-010-0159-3Feo, T., Resende, M.: A probabilistic heuristic for a computationally difficult set covering problem. Oper. Res. Lett. 8, 67–71 (1989)Goossens, J., van Hoesel, C., Kroon, L.: A branch-and-cut approach for solving railway line-planning problems. Transp. Sci. 38, 379–393 (2004)Institute of Electrical and Electronics Engineers: IEEE Standard Computer Dictionary: A Compilation of IEEE Standard Computer Glossaries (1990)Laporte, G., Mesa, J., Perea, F.: A game theoretic framework for the robust railway transit network design problem. Transp. Res., Part B, Methodol. 44, 447–459 (2010)Laporte, G., Marín, A., Mesa, J., Perea, F.: Designing robust rapid transit networks with alternative routes. J. Adv. Transp. 45, 54–65 (2011)Marín, A., García-Ródenas, R.: Location of infrastructure in urban railway networks. Comput. Oper. Res. 36, 1461–1477 (2009)Marín, A., Jaramillo, P.: Urban rapid transit network design: accelerated Benders decomposition. Ann. Oper. Res. 169(1), 35–53 (2009)Marín, A., Mesa, J.A., Perea, F.: Integrating robust railway network design and line planning under failures. Lect. Notes Comput. Sci. 5868, 273–292 (2009)Mauttone, A., Urquhart, M.E.: A route set construction algorithm for the transit network design problem. Comput. Oper. Res. 36, 2440–2449 (2009)Murphey, R., Pardalos, P., Pitsoulis, L.: A GRASP for the multitarget multisensor tracking problem. In: Networks. Discrete Mathematics and Theoretical Computer Science Series, vol. 40, pp. 277–302. American Mathematical Society, Providence (1998)Nesmachnow, S., Cancela, H., Alba, E.: Evolutionary algorithms applied to reliable communication network design. Eng. Optim. 39(7), 831–855 (2007)Schöbel, A., Scholl, S.: Line planning with minimal transfers. In: 5th Workshop on Algorithmic Methods and Models for Optimization of Railways, Number 06901 in Dagstuhl Seminar Proceedings (2006

A review of key planning and scheduling in the rail industry in Europe and UK

Planning and scheduling activities within the rail industry have benefited from developments in computer-based simulation and modelling techniques over the last 25 years. Increasingly, the use of computational intelligence in such tasks is featuring more heavily in research publications. This paper examines a number of common rail-based planning and scheduling activities and how they benefit from five broad technology approaches. Summary tables of papers are provided relating to rail planning and scheduling activities and to the use of expert and decision systems in the rail industry.EPSR

Bus Transit Operational Efficiency Resulting from Passenger Boardings at Park-and-Ride Facilities

In order to save time and money by not driving to an ultimate destination, some urban commuters drive themselves a few miles to specially designated parking lots built for transit customers and located where trains or buses stop. The focus of this paper is the effect Park-and-Ride (P&R) lots have on the efficiency of bus transit as measured in five bus transit systems in the western U.S. This study describes a series of probes with models and data to find objective P&R influence measures that, when combined with other readily-available data, permit a quantitative assessment of the significance of P&R on transit efficiency. The authors developed and describe techniques that examine P&R as an influence on transit boardings at bus stops and on bus boardings along an entire route. The regression results reported are based on the two in-depth case studies for which sufficient data were obtained to examine (using econometric techniques) the effects of park-and-ride availability on bus transit productivity. Both Ordinary Least Square (OLS) regression and Poisson regression are employed. The results from the case studies suggest that availability of parking near bus stops is a stronger influence on transit ridership than residential housing near bus stops. Results also suggest that expanding parking facilities near suburban park-and-ride lots increases the productivity of bus operations as measured by ridership per service hour. The authors also illustrate that reasonable daily parking charges (compared to the cost of driving to much more expensive parking downtown) would provide sufficient capital to build and operate new P&R capacity without subsidy from other revenue sources

Optimal Scheduling of Trains on a Single Line Track

This paper describes the development and use of a model designed to optimise train schedules on single line rail corridors. The model has been developed with two major applications in mind, namely: as a decision support tool for train dispatchers to schedule trains in real time in an optimal way; and as a planning tool to evaluate the impact of timetable changes, as well as railroad infrastructure changes. The mathematical programming model described here schedules trains over a single line track. The priority of each train in a conflict depends on an estimate of the remaining crossing and overtaking delay, as well as the current delay. This priority is used in a branch and bound procedure to allow and optimal solution to reasonable size train scheduling problems to be determined efficiently. The use of the model in an application to a 'real life' problem is discussed. The impacts of changing demand by increasing the number of trains, and reducing the number of sidings for a 150 kilometre section of single line track are discussed. It is concluded that the model is able to produce useful results in terms of optimal schedules in a reasonable time for the test applications shown here

Urban Rapid Transit Network Capacity Expansion

This paper examines a multi-period capacity expansion problem for rapid transit network design. The capacity expansion is realized through the location of train alignments and stations in an urban traffic context by selecting the time periods. The model maximizes the public transportation demand using a limited budget and designing lines for each period. The location problem incorporates the user decisions about mode and route. The network capacity expansion is a long-term planning problem because the network is built over several periods, in which the data (demand, resource price, etc.) are changing like the real problem changes. This complex problem cannot be solved by branch and bound, and for this reason, a heuristic approach has been defined in order to solve it. Both methods have been experimented in test networks

Development and demonstration of an on-board mission planner for helicopters

Mission management tasks can be distributed within a planning hierarchy, where each level of the hierarchy addresses a scope of action, and associated time scale or planning horizon, and requirements for plan generation response time. The current work is focused on the far-field planning subproblem, with a scope and planning horizon encompassing the entire mission and with a response time required to be about two minutes. The far-feld planning problem is posed as a constrained optimization problem and algorithms and structural organizations are proposed for the solution. Algorithms are implemented in a developmental environment, and performance is assessed with respect to optimality and feasibility for the intended application and in comparison with alternative algorithms. This is done for the three major components of far-field planning: goal planning, waypoint path planning, and timeline management. It appears feasible to meet performance requirements on a 10 Mips flyable processor (dedicated to far-field planning) using a heuristically-guided simulated annealing technique for the goal planner, a modified A* search for the waypoint path planner, and a speed scheduling technique developed for this project