Planning the route system for urban buses

Silman, Lionel; Barzily, Zeev; Passy, U.

doi:10.1016/0305-0548(74)90046-x

Cited by 133 publications

(45 citation statements)

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“…Also using a skeleton method to define a bus routes network and its frequencies, Silman et al (1974) aim at minimizing overcrowding and passengers' journey time while satisfying budget constraints. This sequential skeleton method consists in choosing endpoints for a route and then linking them by passing through different zones using shortest paths routes.…”

Section: Heuristic Approachesmentioning

confidence: 99%

Transit network design and scheduling: A global review

Guihaire

Hao

2008

Transportation Research Part A: Policy and Practice

423

313

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This paper presents a global review of the crucial strategic and tactical steps of transit planning: the design and scheduling of the network. These steps influence directly the quality of service through coverage and directness concerns but also the economic profitability of the system since operational costs are highly dependent on the network structure. We first exhibit the context and the goals of strategic and tactical transit planning. We then establish a terminology proposal in order to name sub-problems and thereby structure the review. Then, we propose a classification of 69 approaches dealing with the design, frequencies setting, timetabling of transit lines and their combinations. We provide a descriptive analysis of each work so as to highlight their main characteristics in the frame of a two-fold classification referencing both the problem tackled and the resolution method used. Finally, we expose recent context evolutions and identify some trends for future research. This paper aims to contribute to unification of the field and constitutes a useful complement to the few existing reviews.

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Section: Heuristic Approachesmentioning

confidence: 99%

Transit network design and scheduling: A global review

Guihaire

Hao

2008

Transportation Research Part A: Policy and Practice

423

313

View full text Add to dashboard Cite

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“…This was taken into account in the expression used by Bansal [13]. With regard to user's cost, five elements were considered: the walk time to reach the bus stop, the vehicle's wait time at the bus stop, the travel time on board, the fare paid to use that transportation mode and a non-comfort function expressed as the possibility to travel standing, [26]. The constraints can be classified into 3 types: geometric eqn.…”

Section: Specification Of the Objective Function And The Constraintsmentioning

confidence: 99%

“…However, because of the non-linear and combinatorial nature of the problem, this formulation appears inappropriate [16,26,29]. Moreover, the proposed model is multi-objective, non-linear and is characterised both by integer variables (e.g.…”

Section: Resolution Processmentioning

confidence: 99%

“…They use automatic procedures to generate and to improve the transportation networks, while the complexity of the problem is resolved breaking it down into more manageable parts. Some authors employ this approach [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. In this context, this paper presents a new heuristic model for the TBRND applied to an Italian real case.…”

Section: Introductionmentioning

confidence: 99%

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Transit Bus Route Network Design: a model and its application in a real network

Barabino

2009

WIT Transactions on the Built Environment

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This paper deals with Transit Bus Route Network Design (TBRND) and proposes a new heuristic model for its resolution. Planning a bus network is a coordinate and logical process that leads to the definition of routes, frequencies, timetable plans, vehicles and bus driver scheduling. Routes and frequencies are the most important phases of the planning. Therefore, a model defining a complex objective function has been structured to determine routes and frequencies. This model considers many interesting parameters related to the public transportation network. For its resolution, a complex two-phase heuristic algorithm has been used. In the first one, the route lines are characterized whilst in the second, the frequencies are determined, respecting geometric, operative and congruence constraints. Greedy resolution techniques were employed in the first part, while the second part of the algorithm has been resolved through a random optimization process. The method was implemented and resolved using JAVA language. This model has been experimented on a medium-sized city in Italy, and it has provided some interesting results that make the adopted procedure valid in comparison to the existing network. In particular, they proved effective with specific regard to the business service, standing out for shorter distances covered by the lines, and a 22% reduction of the total travel time against the present scenario.

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“…Early papers on the UTNDP considered only highly specific problem sets [6], [7]. Mandl [8], [9] concentrated on the more generic design of route sets, developing a two-stage solution, first a set of feasible routes is generated, then heuristics are applied to improve the quality of the routes in this set.…”

Section: Introductionmentioning

confidence: 99%

Optimising large scale public transport network design problems using mixed-mode parallel multi-objective evolutionary algorithms

Cooper

John

Lewis

et al. 2014

2014 IEEE Congress on Evolutionary Computation (CEC)

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Abstract-In this paper we present a novel tool, using both OpenMP and MPI protocols, for optimising the efficiency of Urban Transportation Systems within a defined catchment, town or city. We build on a previously presented model which uses a Genetic Algorithm with novel genetic operators to optimise route sets and provide a transport network for a given problem set. This model is then implemented within a Parallel Multi-Objective Genetic Algorithm and demonstrated to be scalable to within the scope of real world, [city-wide], problems. This paper compares and contrasts three methods of parallel distribution of the Genetic Algorithm's computational workload: a job farming algorithm and two variations on an 'Islands' approach. Results are presented in the paper from both single and mixed mode strategies. The results presented are from a range of previously published academic problem sets. Additionally a real world inspired problem set is evaluated and a visualisation of the optimised output is given.

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Planning the route system for urban buses

Cited by 133 publications

References 1 publication

Transit network design and scheduling: A global review

Transit network design and scheduling: A global review

Transit Bus Route Network Design: a model and its application in a real network

Optimising large scale public transport network design problems using mixed-mode parallel multi-objective evolutionary algorithms

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