TY - GEN
T1 - Algorithms for Flows over Time with Scheduling Costs
AU - Frascaria, Dario
AU - Olver, Neil
PY - 2020
Y1 - 2020
N2 - Flows over time have received substantial attention from both an optimization and (more recently) a game-theoretic perspective. In this model, each arc has an associated delay for traversing the arc, and a bound on the rate of flow entering the arc; flows are time-varying. We consider a setting which is very standard within the transportation economic literature, but has received little attention from an algorithmic perspective. The flow consists of users who are able to choose their route but also their departure time, and who desire to arrive at their destination at a particular time, incurring a scheduling cost if they arrive earlier or later. The total cost of a user is then a combination of the time they spend commuting, and the scheduling cost they incur. We present a combinatorial algorithm for the natural optimization problem, that of minimizing the average total cost of all users (i.e., maximizing the social welfare). Based on this, we also show how to set tolls so that this optimal flow is induced as an equilibrium of the underlying game.
AB - Flows over time have received substantial attention from both an optimization and (more recently) a game-theoretic perspective. In this model, each arc has an associated delay for traversing the arc, and a bound on the rate of flow entering the arc; flows are time-varying. We consider a setting which is very standard within the transportation economic literature, but has received little attention from an algorithmic perspective. The flow consists of users who are able to choose their route but also their departure time, and who desire to arrive at their destination at a particular time, incurring a scheduling cost if they arrive earlier or later. The total cost of a user is then a combination of the time they spend commuting, and the scheduling cost they incur. We present a combinatorial algorithm for the natural optimization problem, that of minimizing the average total cost of all users (i.e., maximizing the social welfare). Based on this, we also show how to set tolls so that this optimal flow is induced as an equilibrium of the underlying game.
KW - Flows over time
KW - Tolls
KW - Traffic
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U2 - 10.1007/978-3-030-45771-6_11
DO - 10.1007/978-3-030-45771-6_11
M3 - Conference contribution
AN - SCOPUS:85083991383
SN - 9783030457709
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 130
EP - 143
BT - Integer Programming and Combinatorial Optimization
A2 - Bienstock, Daniel
A2 - Zambelli, Giacomo
PB - Springer
T2 - 21st International Conference on Integer Programming and Combinatorial Optimization, IPCO 2020
Y2 - 8 June 2020 through 10 June 2020
ER -