Abstract
To achieve greater transit-time reduction and improvement in reliability of transport services, there is an increasing need to assist transport planners in understanding the value of punctuality; i.e. the potential improvements, not only to service quality and the consumer but also to the actual profitability of the service. In order for this to be achieved, it is important to understand the network-specific aspects that affect both the ability to decrease transit-time, and the associated cost-benefit of doing so. In this paper, we outline a framework for evaluating the effectiveness of proposed changes to average transit-time, so as to determine the optimal choice of average arrival time subject to desired punctuality levels whilst simultaneously minimizing operational costs. We model the service transit-time variability using a truncated probability density function, and simultaneously compare the trade-off between potential gains and increased service costs, for several commonly employed cost-benefit functions of general form. We formulate this problem as a constrained optimization problem to determine the optimal choice of average transit time, so as to increase the level of service punctuality, whilst simultaneously ensuring a minimum level of cost-benefit to the service operator.
Highlights
In designing a schedule for real-world transport systems, transport planners typically adopt a tactical-planning approach [1,2,3]
When the transport service is delayed, that is when t 2 tp; tmax, the service provider must pay the penalty for the delay, with the penalty cost typically scaling as a function of the number of delay minutes as in Eq 11 [43]
Identifying and obtaining an understanding of underlying transit-factors so as to achieve a quality evaluation of transport services is a key challenge for both short-term and long-term regional and metropolitan freight mobility management and planning
Summary
In designing a schedule for real-world transport systems (e.g. buses, trains, container ships or airlines), transport planners typically adopt a tactical-planning approach [1,2,3]. The underlying characteristics of an optimal transit service is the ability of the service to provide effective standards for management and operation, in such a way as to ensure that negative customer perceptions associated with quality-of-service, (such as unreliability and late-arrival,) are minimized as much as possible These are key factors for determining the customer’s modal choice, transport carrier, and the profits of both service providers and users [3, 7,8,9]. As user demand for transport services continues to grow, there is a pressing need for schedule planners to design schedules in such a way as to incorporate and plan for operational uncertainty This trade-off between variability of punctuality level, transit times and travel costs is discussed in the literatures [10,11,12,13].
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