Intelligent timetable evaluation using fuzzy AHP


There is a substantial body of empirical literature that establishes the benefits of customer satisfaction for enterprises. Among different available options to present our service, selecting the best choice in the customers’ eyes is a vital decision.

Developing appropriate passenger train schedules is counted as one of the major managerial concerns in transportation environment. Although different algorithms have been developed to create predictive schedules for a fleet of passenger trains using different performance indicators, selecting the best one embraces some ambiguities and uncertainties. That is because a one-dimensional objective function may not be sufficient for responding customer concerns.

The main objective of this paper is to propose an approach within the fuzzy AHP framework for tackling the complexity of multidimensional service evaluations, where “sum of weighted waiting times”, “average of unit waiting time” and “maximum ratio of waiting time to journey time” of a schedule are evaluated and the ultimate judgment on goodness of the schedule is made via the aggregation of the performance measures used. The study is based on the knowledge of certain managers and experts in IRC (Iran Railways Corporation) who are aware of available complexities in train scheduling and have been dealing with customers for several years.

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