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The uneven distribution of travel demand is incredibly commonplace in cities, but insufficient attention has been paid to this problem. In this paper, we explore the impact of the uneven distribution of travel demand on an accessible network. A model with a sparse and dense mixed grid transit network based on an uneven distribution of travel demand is proposed to provide a high-performance bus service. The transit network was composed of two parts: a dense grid network in the downtown area and a sparse grid network in the periphery. The objective function of the model included agency cost and passenger cost, where the decision variables were the downtown-to-city ratio, the downtown headway, stop spacing (line spacing), and ratio of the periphery headway to the downtown headway. This study validated the proposed model using the demands of San Francisco. The concentrated spatial demand resulted in a lower total cost, whereas the varying travel demand must be controlled within an appropriate range to maintain the bus performance. The stable bus lines and stops with a variable timetable of the proposed model are profitable for fast-growing cities. [ABSTRACT FROM AUTHOR]

Train delays have a great impact on the schedule of high-speed railways including overall efficiency and the quality of the travel service of the passengers. Therefore, the development of an approach to recover a schedule via timely and rapid operation adjustments must be investigated. In this paper, a complete final real-time adjustment scheme is proposed for the train dispatcher of a railway enterprise for delayed trains. A train operation process model based on the Max-Plus algebra method is proposed. Six operation adjustment strategies are analyzed including section acceleration, operation based on the original timetable, dwell time reduction, increase in overtaking, reduction in overtaking, and train postponement. An approximate model is then built based on the minimum number of delayed trains considering the constraints of the adjustment strategies and the feasible adjusted schemes can be quickly obtained without any record specific time data and constraints. The set of feasible solutions of the approximate model is then regarded as the importation of the second model. In addition, the second model is an optimization model for operation adjustment with the least average delay time of each train at each station by updating the state matrixes of the train operation process model. The algorithms are designed for these models, and this approach can reduce the computation time. Finally, the timetable of the Beijing-Shanghai high-speed railway is considered as the actual case for analysis. Thus, the method was proven feasible for operation adjustment of delayed trains. [ABSTRACT FROM AUTHOR]