Several authors have focused on optimising transit frequencies. Salzborn (1972, 1980) proposed simplified mathematical
models for designing frequencies in order to minimise the bus fleet and passenger waiting times. Furth and Wilson (1982)
devised a mathematical method for optimising the allocation of buses to routes, maximising the net social benefit; they proposed
an algorithm based on Kuhn-Tucker conditions. Han and Wilson (1982) proposed a two-stage heuristic algorithm for
allocating vehicles to routes: in the first stage the minimal frequencies able to satisfy the demand are searched for and in the
second stage the frequencies are increased uniformly until all vehicles of the available fleet are used, taking account of constraints
on total fleet size and route capacities. LeBlanc (1988) formulated a transit network design model for determining
transit frequencies under the assumption of elastic modal split and proposed to solve it by the Hooke–Jeeves algorithm.
Constantin and Florian (1995) formulated a mixed integer programming model for optimising frequencies in order to minimise
passenger total travel and waiting time; they proposed a projected sub-gradient algorithm for solving the problem.
Claessens et al. (1998) developed a mathematical programming model which minimises the operating costs subject to service
constraints and capacity requirements for solving the problem of optimal railway line allocation; the allocation model
was formulated as an integer non-linear programming model and a branch-and-bound procedure was proposed for the solution.
Gao et al. (2004) proposed a bi-level programming model where in the upper level the sum of user costs and operator
costs are minimised and in the lower level a transit assignment model is used for simulating path choices; a heuristic algorithm
based on sensitivity analysis was proposed for solving the problem. Goossens et al. (2004) considered a model formulation
of the line-planning problem where total operating costs were to be minimised; they proposed a branch-and-cut
approach for solving the problem and tested model and algorithm on a real-scale railway network. Goossens et al. (2006)
proposed several models for solving the railway line-planning problem where, over the frequencies of each line, also the
train carriages and the halts of each line may be designed. Yu et al. (2010) proposed a genetic algorithm for solving a bi-level
bus frequency optimisation problem, which aims to minimise the total travel time of passengers subject to the constraint on
the overall fleet size.
Several authors have focused on optimising transit frequencies. Salzborn (1972, 1980) proposed simplified mathematical
models for designing frequencies in order to minimise the bus fleet and passenger waiting times. Furth and Wilson (1982)
devised a mathematical method for optimising the allocation of buses to routes, maximising the net social benefit; they proposed
an algorithm based on Kuhn-Tucker conditions. Han and Wilson (1982) proposed a two-stage heuristic algorithm for
allocating vehicles to routes: in the first stage the minimal frequencies able to satisfy the demand are searched for and in the
second stage the frequencies are increased uniformly until all vehicles of the available fleet are used, taking account of constraints
on total fleet size and route capacities. LeBlanc (1988) formulated a transit network design model for determining
transit frequencies under the assumption of elastic modal split and proposed to solve it by the Hooke–Jeeves algorithm.
Constantin and Florian (1995) formulated a mixed integer programming model for optimising frequencies in order to minimise
passenger total travel and waiting time; they proposed a projected sub-gradient algorithm for solving the problem.
Claessens et al. (1998) developed a mathematical programming model which minimises the operating costs subject to service
constraints and capacity requirements for solving the problem of optimal railway line allocation; the allocation model
was formulated as an integer non-linear programming model and a branch-and-bound procedure was proposed for the solution.
Gao et al. (2004) proposed a bi-level programming model where in the upper level the sum of user costs and operator
costs are minimised and in the lower level a transit assignment model is used for simulating path choices; a heuristic algorithm
based on sensitivity analysis was proposed for solving the problem. Goossens et al. (2004) considered a model formulation
of the line-planning problem where total operating costs were to be minimised; they proposed a branch-and-cut
approach for solving the problem and tested model and algorithm on a real-scale railway network. Goossens et al. (2006)
proposed several models for solving the railway line-planning problem where, over the frequencies of each line, also the
train carriages and the halts of each line may be designed. Yu et al. (2010) proposed a genetic algorithm for solving a bi-level
bus frequency optimisation problem, which aims to minimise the total travel time of passengers subject to the constraint on
the overall fleet size.
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