EVALUATION OF FEEDER BUS SYSTEMS WITH PROBABILISTIC TIME-VARYING DEMANDS AND NONADDITIVE TIME COSTS

Optimal fixed-route conventional bus (CBS) and flexible-route subscription bus (SBS) systems are compared. The average cost, including operator and user costs, is defined as the objective function to be minimized. The decision variables are route spacing and vehicle size in CBS, but service area and vehicle size in SBS. The systems serve probabilistic demand that varies over a 10-h operating period with high demand in the morning and afternoon peak hours. Passengers are assumed to have nonadditive value of time. Average cost per trip is calculated for a numerical example designed to compare the suitability of a particular service under various demand conditions. For this particular example, the CBS provides the lower-cost service. However, the operator can further reduce the cost of daily operation by providing the CBS service in periods of high demand and operating the SBS during off-peak periods. In general, the threshold value of demand at which one system is more cost-effective than another is readily calculated. A sensitivity analysis is conducted to show the effect of varying model parameters on the objective functions and the decision variables

EVALUATION OF FEEDER BUS SYSTEMS WITH PROBABILISTIC TIME-VARYING DEMANDS AND NONADDITIVE VALUE OF TIME

The paper presents a comparison of optimal fixed route conventional bus (CBS) and flexible route subscription (SBS) bus systems. The systems are compared in terms of average cost per trip, including the operator and user costs, as an objective function to be minimized, with vehicle size, route spacing, zone size and headway as the system decision variables. The systems serve probabilistic demand that varies over a ten-hour operating period with a higher number of trips in the morning and afternoon periods. Passengers are assumed to have non-additive value of time. Average cost per trip is calculated for a numerical example in order to compare the suitability of a particular service under various demand conditions. For this particular example, the CBS has the lower cost service. However, the operator can further reduce the cost of daily operation by providing the CBS in periods of high demand and operating the SBS in off-peak periods. In general, the threshold value of demand at which one system is more cost effective than another is readily calculated. A sensitivity analysis is conducted to show the effect of varying model parameters on the objective functions and the decision variables