2020
DOI: 10.1155/2020/9853164
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A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds

Abstract: This study proposes a multiobjective mixed integer linear programming (MOMILP) model for a demand-responsive airport shuttle service. The approach aims to assign a set of alternative fuel vehicles (AFVs) located at different depots to visit each demand point within the specified time and transport all of them to the airport. The proposed model effectively captures the interactions between path selection and environmental protection. Moreover, users with flexible pick-up time windows, the time-varying speed of … Show more

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Cited by 19 publications
(13 citation statements)
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References 38 publications
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“…# of travelling time [18], [19], [23], [24], [30], [32], [33], [35], [36], [39], [42], [46], [47], [58], [61], [66], [73], [76] min. the total travelling cost [8], [11], [12], [20]- [22], [24], [27], [28], [30], [39], [40], [42], [44], [45], [48], [51], [54], [55], [57], [59], [68], [72], [81] min. the rental cost [28], [59] min.…”
Section: Discussionmentioning
confidence: 99%
“…# of travelling time [18], [19], [23], [24], [30], [32], [33], [35], [36], [39], [42], [46], [47], [58], [61], [66], [73], [76] min. the total travelling cost [8], [11], [12], [20]- [22], [24], [27], [28], [30], [39], [40], [42], [44], [45], [48], [51], [54], [55], [57], [59], [68], [72], [81] min. the rental cost [28], [59] min.…”
Section: Discussionmentioning
confidence: 99%
“…Similarly, Wei et al fully considered the time-varying speed and time window of the vehicle and proposed a heuristic-based nondominated ranking genetic algorithm to find the Pareto optimal solution in a reasonable time [18]. Liu Zhang constructed an urban cold chain transportation model, with the objective function of minimizing the total cost in view of the time-dependent nature of urban cold chain transportation and the time-varying nature of urban road speed, and an artificial immune particle swarm optimization algorithm to solve the model [19].…”
Section: Review Of the Literaturementioning
confidence: 99%
“…Constraint (11) defines the mathematical relationship between the departure and arrival times of each bus run serial number of the feeder transit. Constraint (12) defines the mathematical relationship between the arrival time of a bus run serial number of the feeder transit and the express line, which guarantees that the passenger waiting time is zero.…”
Section: Optimization Modelmentioning
confidence: 99%
“…Some studies have proposed machine learning [27], hybrid evolutionary [28], and Tabu search [29,30] methods for the dial-a-ride problem; GA [12,31] and heuristic algorithm [11,24] are among the most successful approximate approaches for solving the dial-a-ride problem. GA was tested on a set of medium-scale problem scenarios, and it was found to be accessible and efficient.…”
Section: Solution Algorithmmentioning
confidence: 99%
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