Competitive Online Transportation Simplified
By: Stephen Arndt , Benjamin Moseley , Kirk Pruhs and more
Potential Business Impact:
Finds best parking spots for cars arriving.
The setting for the online transportation problem is a metric space $M$, populated by $m$ parking garages of varying capacities. Over time cars arrive in $M$, and must be irrevocably assigned to a parking garage upon arrival in a way that respects the garage capacities. The objective is to minimize the aggregate distance traveled by the cars. In 1998, Kalyanasundaram and Pruhs conjectured that there is a $(2m-1)$-competitive deterministic algorithm for the online transportation problem, matching the optimal competitive ratio for the simpler online metric matching problem. Recently, Harada and Itoh presented the first $O(m)$-competitive deterministic algorithm for the online transportation problem. Our contribution is an alternative algorithm design and analysis that we believe is simpler.
Similar Papers
Online 3-Taxi on General Metrics
Data Structures and Algorithms
Makes 3 taxis find passengers faster.
Online Metric TSP
Data Structures and Algorithms
Helps sort items arriving one by one.
Lower Bound for Online MMS Assignment of Indivisible Chores
CS and Game Theory
Makes chores fairer when done one by one.