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2019
DOI: 10.3390/sym11040514
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A Multi-Objective Programming Approach to Design Feeder Bus Route for High-Speed Rail Stations

Abstract: The quality of route design can greatly affect the operational efficiency of feeder bus service for high-speed rail stations. A bi-objective optimization formulation is established to consider the trade-off between two conflicting optimization objectives, namely maximizing the travel demand that can be served and minimizing the feeder bus route length. The Pareto optimal solutions of the discrete mathematical formulation are generated by the exact ε-constraint method. We test the proposed approach with a numer… Show more

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Cited by 7 publications
(5 citation statements)
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References 37 publications
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“…Feng et al set up a new bus network optimization model that reduced passenger transit time and transfer times by optimizing route design [25]. Similarly, in the two-level optimization model established by Guo et al, the researchers regarded maximizing the serviceable demand as the upper objective and minimizing the length of the receiving bus line as the lower objective, and they fnally generated the route scheme under the actual road network conditions [26]. To solve these transit route design models, a common solution includes the generation of an initial set of routes, the selection of feasible routes based on objectives and constraints, and the evaluation of efciency.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Feng et al set up a new bus network optimization model that reduced passenger transit time and transfer times by optimizing route design [25]. Similarly, in the two-level optimization model established by Guo et al, the researchers regarded maximizing the serviceable demand as the upper objective and minimizing the length of the receiving bus line as the lower objective, and they fnally generated the route scheme under the actual road network conditions [26]. To solve these transit route design models, a common solution includes the generation of an initial set of routes, the selection of feasible routes based on objectives and constraints, and the evaluation of efciency.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Guo et al [25] studied the integrated optimization of community shuttle stops and routes, and developed a non-dominated sorting genetic based algorithm to solve the proposed bi-objective programing formulation. Guo et al [26] determined the stop location and running route of the feeder bus service for high-speed rail stations through a bi-objective mathematical model, and used the exact ε-constraint method to solve the problem. However, there is less research on the location optimization of parcel lockers.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The optimization goal is to minimize the disutility of passengers and the operation cost. For type P passengers, the disutility is measured by the weighted sum of passengers' arrival time deviations and their ride time deviations (see (36)). Similarly, the disutility of type D passengers is calculated as the weighted sum of passenger's boarding time deviations and their ride time deviations (see (37)).…”
Section: Model Formulation a Objective Functionmentioning
confidence: 99%
“…Focus on FBNDP, [35] optimized the collection points and vehicle routes to minimize the access cost of passengers and the operation cost. Guo et al designed an exact -constraint method to solve the FBNDP, and discussed the influence of maximum walk time of passengers and route length constraint [36]. Lee et al extended the regional DRC to allow alternative transit stations for passengers [37].…”
Section: Introductionmentioning
confidence: 99%