Abstract
The problem of dynamic transit scheduling is addressed, and a method for transient and steady-state solutions is developed. The dynamic demand-supply formulation employed is based on previously calibrated disaggregate demand specifications. The existence and feasibility of solutions are examined, and stability conditions are derived. Numerical examples for both urban and rural conditions are given. The new methodology does not require time-series endogenous data but only initial conditions to provide long- or short-term scheduling plans. Futhermore, it takes into account passenger demand fluctuations and explicitly deals with management responsiveness and time lags in implementing scheduling decisions. Owing to its dynamic nature the methodology can be used as a design tool in transit scheduling and for assessing the effects of time-varying exogenous events such as gasoline price fluctuations, transport budget restrictions and other contingencies.
| Original language | English |
|---|---|
| Pages (from-to) | 95-111 |
| Number of pages | 17 |
| Journal | Transportation Research, Series B: Methodological |
| Volume | 19 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1985 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Management Science and Operations Research
- Transportation
- Engineering(all)
- Earth and Planetary Sciences(all)
- Environmental Science(all)
Cite this
Dynamic transit scheduling under efficiency constraints. / Stephanedes, Yorgos J.; Michalopoulos, Panos G.; Bountis, Tassos.
In: Transportation Research, Series B: Methodological, Vol. 19, No. 2, 1985, p. 95-111.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Dynamic transit scheduling under efficiency constraints
AU - Stephanedes, Yorgos J.
AU - Michalopoulos, Panos G.
AU - Bountis, Tassos
PY - 1985
Y1 - 1985
N2 - The problem of dynamic transit scheduling is addressed, and a method for transient and steady-state solutions is developed. The dynamic demand-supply formulation employed is based on previously calibrated disaggregate demand specifications. The existence and feasibility of solutions are examined, and stability conditions are derived. Numerical examples for both urban and rural conditions are given. The new methodology does not require time-series endogenous data but only initial conditions to provide long- or short-term scheduling plans. Futhermore, it takes into account passenger demand fluctuations and explicitly deals with management responsiveness and time lags in implementing scheduling decisions. Owing to its dynamic nature the methodology can be used as a design tool in transit scheduling and for assessing the effects of time-varying exogenous events such as gasoline price fluctuations, transport budget restrictions and other contingencies.
AB - The problem of dynamic transit scheduling is addressed, and a method for transient and steady-state solutions is developed. The dynamic demand-supply formulation employed is based on previously calibrated disaggregate demand specifications. The existence and feasibility of solutions are examined, and stability conditions are derived. Numerical examples for both urban and rural conditions are given. The new methodology does not require time-series endogenous data but only initial conditions to provide long- or short-term scheduling plans. Futhermore, it takes into account passenger demand fluctuations and explicitly deals with management responsiveness and time lags in implementing scheduling decisions. Owing to its dynamic nature the methodology can be used as a design tool in transit scheduling and for assessing the effects of time-varying exogenous events such as gasoline price fluctuations, transport budget restrictions and other contingencies.
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UR - http://www.scopus.com/inward/citedby.url?scp=0022268512&partnerID=8YFLogxK
U2 - 10.1016/0191-2615(85)90017-7
DO - 10.1016/0191-2615(85)90017-7
M3 - Article
AN - SCOPUS:0022268512
VL - 19
SP - 95
EP - 111
JO - Transportation Research, Series B: Methodological
JF - Transportation Research, Series B: Methodological
SN - 0191-2615
IS - 2
ER -