3 research outputs found
Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΡΠΎΠ·ΠΏΠΎΠ²ΡΡΠ΄ΠΆΠ΅Π½Π½Ρ Π·Π°ΡΡΠΈΠΌΠΊΠΈ Ρ Π½Π΅ΡΠΈΠΊΠ»ΡΡΠ½ΠΎΠΌΡ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π½Π° Π·Π°Π»ΡΠ·Π½ΠΈΡΡΡ Π·ΠΌΡΡΠ°Π½ΠΎΠ³ΠΎ ΡΡΡ Ρ
The main goal of present study is to develop a method for modeling delay propagation in non-cyclic train scheduling on a railroad network with mixed traffic. This will make it possible to explore the dynamics of delay transfer between trains and to identify the most vulnerable points in the timetable of trains. We have devised a method for modeling delay propagation in non-cyclic train scheduling for the rail networks with mixed traffic. It is proposed to apply as a basis of the developed method a mathematical model for the construction of a non-cyclic train timetable. A distinctive feature of the objective function of the mathematical model is taking into consideration the patterns of building a non-cyclic train timetable under conditions of mixed traffic of passenger and heavy-weight or multi-car freight trains, for which it is important to minimize the cost of stopping during motion. The proposed mathematical model was solved based on the multiagent optimization. To account for delay propagation on the railroad network of great dimensionality, we devised a procedure for connecting interdependent sections, which makes it possible to decompose the general problem based on the construction of schedule of trains for separate estimated sections taking into consideration the network effect. We performed an analysis of the dynamics of propagation of secondary delays in non-cyclic train scheduling with detailed patterns of changes in all parameters in time and space. We obtained dependences of the number and duration of delayed trains on the point of occurrence in the timetable of trains along the estimated line of the Ukrainian railroad network. The approach proposed allows the automatization of determining a time reserve in the standard non-cyclic train scheduling based on forecasting the consequences of train delays.ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅ΡΠΎΠ΄ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ Π·Π°Π΄Π΅ΡΠΆΠΊΠΈ Π² Π½Π΅ΡΠΈΠΊΠ»ΠΈΡΠ΅ΡΠΊΠΎΠΌ Π³ΡΠ°ΡΠΈΠΊΠ΅ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Ρ ΡΡΠ΅ΡΠΎΠΌ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠΎΠ±Π΅Π½ΠΎΡΡΠ΅ΠΉ ΠΆΠ΅Π»Π΅Π·Π½ΠΎΠ΄ΠΎΡΠΎΠΆΠ½ΠΎΠΉ ΡΠ΅ΡΠΈ ΡΠΌΠ΅ΡΠ°Π½Π½ΠΎΠ³ΠΎ ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΡΠΊΠΎΠ³ΠΎ ΠΈ Π³ΡΡΠ·ΠΎΠ²ΠΎΠ³ΠΎ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ. Π Π°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π° ΠΏΡΠΎΡΠ΅Π΄ΡΡΠ° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π²Π»ΠΈΡΠ½ΠΈΡ Π·Π°Π΄Π΅ΡΠΆΠΊΠΈ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Π² Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΌ Π³ΡΠ°ΡΠΈΠΊΠ΅ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ Π³ΡΠ°ΡΠΈΠΊΠ° Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Ρ ΡΡΠ΅ΡΠΎΠΌ Π·Π°Π΄Π°Π½ΠΎΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π·Π°Π΄Π΅ΡΠΆΠΊΠΈ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠ΅ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ Π·Π°Π΄Π΅ΡΠΆΠΊΠΈ Π² Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΌ Π³ΡΠ°ΡΠΈΠΊΠ΅ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Π½Π° ΠΆΠ΅Π»Π΅Π·Π½ΠΎΠ΄ΠΎΡΠΎΠΆΠ½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠΈ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΏΡΠΎΡΡΠΆΠ΅Π½Π½ΠΎΡΡΠΈΠΠ°ΠΏΡΠΎΠΏΠΎΠ½ΠΎΠ²Π°Π½ΠΎ ΠΌΠ΅ΡΠΎΠ΄ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΡΠΎΠ·ΠΏΠΎΠ²ΡΡΠ΄ΠΆΠ΅Π½Π½Ρ Π·Π°ΡΡΠΈΠΌΠΊΠΈ Ρ Π½Π΅ΡΠΈΠΊΠ»ΡΡΠ½ΠΎΠΌΡ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ
Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π· ΡΡΠ°Ρ
ΡΠ²Π°Π½Π½ΡΠΌ ΡΠ΅Ρ
Π½ΡΡΠ½ΠΈΡ
ΡΠ° ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΡΠ½ΠΈΡ
ΠΎΡΠΎΠ±Π»ΠΈΠ²ΠΎΡΡΠ΅ΠΉ Π·Π°Π»ΡΠ·Π½ΠΈΡΠ½ΠΎΡ ΠΌΠ΅ΡΠ΅ΠΆΡ Π·ΠΌΡΡΠ°Π½ΠΎΠ³ΠΎ ΡΡΡ
Ρ ΠΏΠ°ΡΠ°ΠΆΠΈΡΡΡΠΊΠΈΡ
Ρ Π²Π°Π½ΡΠ°ΠΆΠ½ΠΈΡ
ΠΏΠΎΡΠ·Π΄ΡΠ². Π ΠΎΠ·ΡΠΎΠ±Π»Π΅Π½ΠΎ ΠΏΡΠΎΡΠ΅Π΄ΡΡΡ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π²ΠΏΠ»ΠΈΠ²Ρ Π·Π°ΡΡΠΈΠΌΠΊΠΈ ΠΏΠΎΡΠ·Π΄ΡΠ² Ρ Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΌΡ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ
Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΠΉΠ½ΠΎΡ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½ΠΎΡ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ
Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π· ΡΡΠ°Ρ
ΡΠ²Π°Π½Π½Ρ Π·Π°Π΄Π°Π½ΠΎΡ ΠΏΠ΅ΡΠ²ΠΈΠ½Π½ΠΎΡ Π·Π°ΡΡΠΈΠΌΠΊΠΈ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Ρ Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΠΏΠΎΡΠΈΡΠ΅Π½Π½Ρ Π·Π°ΡΡΠΈΠΌΠΊΠΈ ΠΏΠΎΡΠ·Π΄ΡΠ² Ρ Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΌΡ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ
Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π· ΡΡΠ°Ρ
ΡΠ²Π°Π½Π½ΡΠΌ Π²Π·Π°ΡΠΌΠΎΡΠ²βΡΠ·ΠΊΠΈ Π·Π°Π»ΡΠ·Π½ΠΈΡΠ½ΠΈΡ
Π΄ΡΠ»ΡΠ½ΠΈΡ
Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΡΠΎΠ·ΠΏΠΎΠ²ΡΡΠ΄ΠΆΠ΅Π½Π½Ρ Π·Π°ΡΡΠΈΠΌΠΊΠΈ Ρ Π½Π΅ΡΠΈΠΊΠ»ΡΡΠ½ΠΎΠΌΡ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π½Π° Π·Π°Π»ΡΠ·Π½ΠΈΡΡΡ Π·ΠΌΡΡΠ°Π½ΠΎΠ³ΠΎ ΡΡΡ Ρ
The main goal of present study is to develop a method for modeling delay propagation in non-cyclic train scheduling on a railroad network with mixed traffic. This will make it possible to explore the dynamics of delay transfer between trains and to identify the most vulnerable points in the timetable of trains. We have devised a method for modeling delay propagation in non-cyclic train scheduling for the rail networks with mixed traffic. It is proposed to apply as a basis of the developed method a mathematical model for the construction of a non-cyclic train timetable. A distinctive feature of the objective function of the mathematical model is taking into consideration the patterns of building a non-cyclic train timetable under conditions of mixed traffic of passenger and heavy-weight or multi-car freight trains, for which it is important to minimize the cost of stopping during motion. The proposed mathematical model was solved based on the multiagent optimization. To account for delay propagation on the railroad network of great dimensionality, we devised a procedure for connecting interdependent sections, which makes it possible to decompose the general problem based on the construction of schedule of trains for separate estimated sections taking into consideration the network effect. We performed an analysis of the dynamics of propagation of secondary delays in non-cyclic train scheduling with detailed patterns of changes in all parameters in time and space. We obtained dependences of the number and duration of delayed trains on the point of occurrence in the timetable of trains along the estimated line of the Ukrainian railroad network. The approach proposed allows the automatization of determining a time reserve in the standard non-cyclic train scheduling based on forecasting the consequences of train delays.ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅ΡΠΎΠ΄ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ Π·Π°Π΄Π΅ΡΠΆΠΊΠΈ Π² Π½Π΅ΡΠΈΠΊΠ»ΠΈΡΠ΅ΡΠΊΠΎΠΌ Π³ΡΠ°ΡΠΈΠΊΠ΅ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Ρ ΡΡΠ΅ΡΠΎΠΌ ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΎΡΠΎΠ±Π΅Π½ΠΎΡΡΠ΅ΠΉ ΠΆΠ΅Π»Π΅Π·Π½ΠΎΠ΄ΠΎΡΠΎΠΆΠ½ΠΎΠΉ ΡΠ΅ΡΠΈ ΡΠΌΠ΅ΡΠ°Π½Π½ΠΎΠ³ΠΎ ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΡΠΊΠΎΠ³ΠΎ ΠΈ Π³ΡΡΠ·ΠΎΠ²ΠΎΠ³ΠΎ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ. Π Π°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π° ΠΏΡΠΎΡΠ΅Π΄ΡΡΠ° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π²Π»ΠΈΡΠ½ΠΈΡ Π·Π°Π΄Π΅ΡΠΆΠΊΠΈ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Π² Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΌ Π³ΡΠ°ΡΠΈΠΊΠ΅ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ Π³ΡΠ°ΡΠΈΠΊΠ° Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Ρ ΡΡΠ΅ΡΠΎΠΌ Π·Π°Π΄Π°Π½ΠΎΠΉ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π·Π°Π΄Π΅ΡΠΆΠΊΠΈ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠ΅ ΡΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ Π·Π°Π΄Π΅ΡΠΆΠΊΠΈ Π² Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΌ Π³ΡΠ°ΡΠΈΠΊΠ΅ Π΄Π²ΠΈΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠ΅Π·Π΄ΠΎΠ² Π½Π° ΠΆΠ΅Π»Π΅Π·Π½ΠΎΠ΄ΠΎΡΠΎΠΆΠ½ΠΎΠΉ Π»ΠΈΠ½ΠΈΠΈ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΏΡΠΎΡΡΠΆΠ΅Π½Π½ΠΎΡΡΠΈΠΠ°ΠΏΡΠΎΠΏΠΎΠ½ΠΎΠ²Π°Π½ΠΎ ΠΌΠ΅ΡΠΎΠ΄ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΡΠΎΠ·ΠΏΠΎΠ²ΡΡΠ΄ΠΆΠ΅Π½Π½Ρ Π·Π°ΡΡΠΈΠΌΠΊΠΈ Ρ Π½Π΅ΡΠΈΠΊΠ»ΡΡΠ½ΠΎΠΌΡ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ
Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π· ΡΡΠ°Ρ
ΡΠ²Π°Π½Π½ΡΠΌ ΡΠ΅Ρ
Π½ΡΡΠ½ΠΈΡ
ΡΠ° ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΡΠ½ΠΈΡ
ΠΎΡΠΎΠ±Π»ΠΈΠ²ΠΎΡΡΠ΅ΠΉ Π·Π°Π»ΡΠ·Π½ΠΈΡΠ½ΠΎΡ ΠΌΠ΅ΡΠ΅ΠΆΡ Π·ΠΌΡΡΠ°Π½ΠΎΠ³ΠΎ ΡΡΡ
Ρ ΠΏΠ°ΡΠ°ΠΆΠΈΡΡΡΠΊΠΈΡ
Ρ Π²Π°Π½ΡΠ°ΠΆΠ½ΠΈΡ
ΠΏΠΎΡΠ·Π΄ΡΠ². Π ΠΎΠ·ΡΠΎΠ±Π»Π΅Π½ΠΎ ΠΏΡΠΎΡΠ΅Π΄ΡΡΡ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π²ΠΏΠ»ΠΈΠ²Ρ Π·Π°ΡΡΠΈΠΌΠΊΠΈ ΠΏΠΎΡΠ·Π΄ΡΠ² Ρ Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΌΡ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ
Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΠΉΠ½ΠΎΡ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½ΠΎΡ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ
Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π· ΡΡΠ°Ρ
ΡΠ²Π°Π½Π½Ρ Π·Π°Π΄Π°Π½ΠΎΡ ΠΏΠ΅ΡΠ²ΠΈΠ½Π½ΠΎΡ Π·Π°ΡΡΠΈΠΌΠΊΠΈ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Ρ Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΠ°Π»ΡΠ½Ρ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ΠΏΠΎΡΠΈΡΠ΅Π½Π½Ρ Π·Π°ΡΡΠΈΠΌΠΊΠΈ ΠΏΠΎΡΠ·Π΄ΡΠ² Ρ Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΠΌΡ Π³ΡΠ°ΡΡΠΊΡ ΡΡΡ
Ρ ΠΏΠΎΡΠ·Π΄ΡΠ² Π· ΡΡΠ°Ρ
ΡΠ²Π°Π½Π½ΡΠΌ Π²Π·Π°ΡΠΌΠΎΡΠ²βΡΠ·ΠΊΠΈ Π·Π°Π»ΡΠ·Π½ΠΈΡΠ½ΠΈΡ
Π΄ΡΠ»ΡΠ½ΠΈΡ