20 research outputs found
Bus Frequency Optimization: When Waiting Time Matters in User Satisfaction
Reorganizing bus frequency to cater for the actual travel demand can save the
cost of the public transport system significantly. Many, if not all, existing
studies formulate this as a bus frequency optimization problem which tries to
minimize passengers' average waiting time. However, many investigations have
confirmed that the user satisfaction drops faster as the waiting time
increases. Consequently, this paper studies the bus frequency optimization
problem considering the user satisfaction. Specifically, for the first time to
our best knowledge, we study how to schedule the buses such that the total
number of passengers who could receive their bus services within the waiting
time threshold is maximized. We prove that this problem is NP-hard, and present
an index-based algorithm with approximation ratio. By exploiting the
locality property of routes in a bus network, we propose a partition-based
greedy method which achieves a approximation ratio. Then we
propose a progressive partition-based greedy method to further improve the
efficiency while achieving a approximation ratio.
Experiments on a real city-wide bus dataset in Singapore verify the efficiency,
effectiveness, and scalability of our methods
Application of functionalized nanofluid in thermosyphon
A water-based functionalized nanofluid was made by surface functionalizing the ordinary silica nanoparticles. The functionalized nanofluid can keep long-term stability. and no sedimentation was observed. The functionalized nanofluid as the working fluid is applied in a thermosyphon to understand the effect of this special nanofluid on the thermal performance of the thermosyphon. The experiment was carried out under steady operating pressures. The same work was also explored for traditional nanofluid (consisting of water and the same silica nanoparticles without functionalization) for comparison. Results indicate that a porous deposition layer exists on the heated surface of the evaporator during the operating process using traditional nanofluid; however, no coating layer exists for functionalized nanofluid. Functionalized nanofluid can enhance the evaporating heat transfer coefficient, while it has generally no effect on the maximum heat flux. Traditional nanofluid deteriorates the evaporating heat transfer coefficient but enhances the maximum heat flux. The existence of the deposition layer affects mainly the thermal performance, and no meaningful nanofluid effect is found in the present study
BUS MAINTENANCE SYSTEMS AND MAINTENANCE SCHEDULING: MODEL FORMULATIONS AND SOLUTIONS
The problem of scheduling bus maintenance activities is an important component in the bus transit operations planning process. This paper presents a mathematical programming approach to this problem. This approach takes as input a given daily operating schedule for all buses assigned to a depot along with available maintenance resources. It then attempts to design daily inspection and maintenance schedules for the buses that are due for inspection so as to minimize the interruptions in the daily bus operating schedule and maximize the utilization of the maintenance facilities. Three integer programming formulations are presented and different properties of the problem are discussed. Several heuristic methods are presented and tested. Some of these procedures produce very close to optimal solutions very efficiently. In some cases, the computational times required to obtain these solutions are less than 1% of the computational time required for the conventional branch and bound algorithm. A case study based on an actual 181-bus transit property was used to compare the efficiency and effectiveness of the proposed solution procedures
Last train timetable optimization considering detour routing strategy in an urban rail transit network
Scheduling overnight trains for improving both last and first train services in an urban subway network
Bus frequency optimization: When waiting time matters in user satisfaction
Reorganizing bus frequency to cater for the actual travel demand can save the
cost of the public transport system significantly. Many, if not all, existing
studies formulate this as a bus frequency optimization problem which tries to
minimize passengers' average waiting time. However, many investigations have
confirmed that the user satisfaction drops faster as the waiting time
increases. Consequently, this paper studies the bus frequency optimization
problem considering the user satisfaction. Specifically, for the first time to
our best knowledge, we study how to schedule the buses such that the total
number of passengers who could receive their bus services within the waiting
time threshold is maximized. We prove that this problem is NP-hard, and present
an index-based algorithm with approximation ratio. By exploiting the
locality property of routes in a bus network, we propose a partition-based
greedy method which achieves a approximation ratio. Then we
propose a progressive partition-based greedy method to further improve the
efficiency while achieving a approximation ratio.
Experiments on a real city-wide bus dataset in Singapore verify the efficiency,
effectiveness, and scalability of our methods