Abstract
The transit network design problem involves determining a certain number of routes to operate in an urban area to balance the costs of the passengers and the operator. In this paper, we simultaneously determine the route structure of each route and the number of routes in the final solution. A novel initial route set generation algorithm and a route set size alternating heuristic are embedded into a nondominated sorting genetic algorithm-II- (NSGA-II-) based solution framework to produce the approximate Pareto front. The initial route set generation algorithm aims to generate high-quality initial solutions for succeeding optimization procedures. To explore the solution space and to have solutions with a different number of routes, a route set size alternating heuristic is developed to change the number of routes in a solution by adding or deleting one route. Experiments were performed on Mandl’s network and four larger Mumford’s networks. Compared with a fixed route set size approach, the proposed NSGA-II-based solution method can produce an approximate Pareto front with much higher solution quality as well as improved computation efficiency.
Highlights
Followed by frequency setting, timetable development, bus scheduling, and driver scheduling, the transit network design problem (TNDP) [1] aims to determine a set of routes to operate in an urban area to balance the costs of the passengers and the operator. e performance of the succeeding four stages highly depends on the quality of the results of the transit network design. us, the TNDP has been continuously studied during the last five decades
E main contributions of this research are threefold: (a) the development of an initial route set generation algorithm to produce high-quality initial solutions for the TNDP; (b) the proposal of a route set size alternating heuristic to alternate the number of routes in a solution during the optimization procedure; and (c) the illustration of the applicability of the proposed solution method in five networks with different scales
An integrated solution method is proposed to simultaneously solve the transit network design problem and the route set size determination problem. e solution method includes a novel initial route set generation algorithm that aims to produce high-quality initial solutions for the optimization algorithm and to explore the solution space with a different number of routes, and it contains a route set size alternating heuristic to alternate the number of routes in a solution. ese two algorithms are embedded into NSGAII-based solution framework to find the approximate Pareto front in terms of both objectives
Summary
Timetable development, bus scheduling, and driver scheduling, the transit network design problem (TNDP) [1] aims to determine a set of routes to operate in an urban area to balance the costs of the passengers and the operator. e performance of the succeeding four stages highly depends on the quality of the results of the transit network design. us, the TNDP has been continuously studied during the last five decades. Timetable development, bus scheduling, and driver scheduling, the transit network design problem (TNDP) [1] aims to determine a set of routes to operate in an urban area to balance the costs of the passengers and the operator. Despite the attention given TNDP, the determination of a suitable number of routes (or a range) for a specific network has received little attention. E route set size is an important parameter in the transit network design because of the following reasons. There is a trade-off between the route set size and the average travel time, which is an important indicator of the transit network performance. Optimizing the route set size can lead to solutions with a wide range of trade-off levels between the operator cost and the passenger cost
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