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
“…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.…”
Rural tourism bus routes are an essential component of rural public transport systems, intending to serve tourist trips with passengers moving between critical regional transport nodes and tourist attractions. This paper presents a methodology for the optimal design of rural tourism bus routes by minimizing total travel costs for tourists and maximizing the total quality of tourism bus services. Road scenery, road design attributes, and route popularity elements are integrated into the evaluation of tourism bus service quality. The constraints for the bus route planning and tourism demand are taken into account to guarantee the rational design of rural tourism bus routes. A solution approach is put forward based on the initial solution set generation procedure and strengthens the elitist genetic algorithm. Finally, the bus network in a rural tourism destination of Nanjing is taken as the case study to validate the feasibility and efficiency of the proposed model.
“…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.…”
Rural tourism bus routes are an essential component of rural public transport systems, intending to serve tourist trips with passengers moving between critical regional transport nodes and tourist attractions. This paper presents a methodology for the optimal design of rural tourism bus routes by minimizing total travel costs for tourists and maximizing the total quality of tourism bus services. Road scenery, road design attributes, and route popularity elements are integrated into the evaluation of tourism bus service quality. The constraints for the bus route planning and tourism demand are taken into account to guarantee the rational design of rural tourism bus routes. A solution approach is put forward based on the initial solution set generation procedure and strengthens the elitist genetic algorithm. Finally, the bus network in a rural tourism destination of Nanjing is taken as the case study to validate the feasibility and efficiency of the proposed model.
“…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.…”
The movable unit equipped with a set of lockers has been recently developed as a new mode to improve the efficiency of the last mile delivery. Locating a set of movable parcel locker units appropriately is a fundamental factor to promote the merits of movable parcel lockers. However, the difficulty in determining where to locate movable parcel locker units arises from the stochastic characteristics of demands. Therefore, we propose a robust optimization approach to determine the number of movable parcel locker units and their locations simultaneously with the aim to minimize the operating cost under stochastic demands and mobility restrictions. To reduce the complexity of the optimization model, the non-linear constraints have been transformed into the linear counterparts, resulting in an integer linear programming (ILP) model that can be solved by commercially available mathematical programming solvers. The results from the numerical examples indicate the proposed approach can obtain high robustness with a small extra cost within reasonable time. In addition, it is found that if each unit is equipped with more lockers, fewer movable parcel locker units are required to accommodate the demands with less operating cost, as the demand points can be clustered into a few intensive self-pickup sites.
“…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].…”
This study concentrates on the routing and scheduling problem of Demand Responsive Connector to build feeder plans for people traveling from and to transit hub. An in-depth analysis on the characteristics of feeder services was implemented to inspire the compatibility-based algorithm design. With the goal of reducing operating cost and passenger inconvenience, the proposed algorithm took several factors critical to the real-word operation into consideration, such as double time window assurance (the time constraints at the beginning and end of passenger travels), the flexibility of feeder plans, and the number of vehicles. Our method was validated on numerical instances of 400, 600, 800 and 1000 passengers. Simulation results show that the compatibility-based algorithm can effectively reduce the number of vehicles with acceptable increase of passengers' inconvenience, and can improve the algorithm efficiency considerably. In addition, the setting of flexible time window of shutter plan can hold some elasticity for feeder services. Sensitivity analysis was conducted to help service providers evaluate the trade-off between the operation cost and level of service. INDEX TERMS Compatibility-based approach, demand responsive connector, routing and scheduling.
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