Premium
Online traveling salesman problems with rejection options
Author(s) -
Jaillet Patrick,
Lu Xin
Publication year - 2014
Publication title -
networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.977
H-Index - 64
eISSN - 1097-0037
pISSN - 0028-3045
DOI - 10.1002/net.21559
Subject(s) - competitive analysis , online algorithm , travelling salesman problem , metric (unit) , computer science , metric space , time complexity , upper and lower bounds , space (punctuation) , real line , order (exchange) , line (geometry) , mathematical optimization , mathematics , algorithm , combinatorics , discrete mathematics , economics , mathematical analysis , operations management , geometry , finance , operating system
In this article, we consider online versions of the traveling salesman problem on metric spaces for which requests to visit points are not mandatory. Associated with each request is a penalty (if rejected). Requests are revealed over time (at their release dates) to a server who must decide which requests to accept and serve in order to minimize a linear combination of the time to serve all accepted requests and the total penalties of all rejected requests. In the basic online version of the problem, a request can be accepted any time after its release date. In the real‐time online version, a request must be accepted or rejected at the time of its release date. For the basic version, we provide a best possible 2‐competitive online algorithm for the problem on a general metric space. For the real‐time version, we first consider special metric spaces: on the nonnegative real line, we provide a best possible 2.5‐competitive polynomial time online algorithm; on the real line, we prove a lower bound of 2.64 on any competitive ratios and give a 3‐competitive online algorithm. We then consider the case of a general metric space and prove a Ω ( ln n ) lower bound on the competitive ratio of any online algorithms. Finally, among the restricted class of online algorithms with prior knowledge about the total number of requests n , we propose an asymptotically best possible O ( ln n ) ‐competitive algorithm. © 2014 Wiley Periodicals, Inc. NETWORKS, Vol. 64(2), 84–95 2014