Online Routing Problems: Value of Advanced Information as Improved Competitive Ratios

We consider online versions of the traveling salesman problem (TSP) and traveling repairman problem (TRP) where instances are not known in advance. Cities (points) to be visited are revealed over time, while the server is en route serving previously released requests. These problems are known in the literature as the online TSP (TRP, respectively). The corresponding offline problems are the TSP (TRP) with release dates, problems where each point has to be visited at or after a given release date. In the current literature, the assumption is that a request becomes known at the time of its release date. In this paper we introduce the notion of a requests disclosure date, the time when a citys location and release date are revealed to the server. In a variety of disclosure date scenarios and metric spaces, we give new online algorithms and quantify the value of this advanced information in the form of improved competitive ratios. We also provide a general result on polynomial-time online algorithms for the online TSP.

[1]  Leen Stougie,et al.  On-line single-server dial-a-ride problems , 2001, Theor. Comput. Sci..

[2]  John N. Tsitsiklis,et al.  Special cases of traveling salesman and repairman problems with time windows , 1992, Networks.

[3]  N. Biggs THE TRAVELING SALESMAN PROBLEM A Guided Tour of Combinatorial Optimization , 1986 .

[4]  D. Bertsimas Probabilistic combinatorial optimization problems , 1988 .

[5]  M Maarten Lipmann The on-line travelling salesman problem on the line , 2003 .

[6]  Marius M. Solomon,et al.  Routing and scheduling on a shoreline with release times , 1990 .

[7]  Sanjeev Arora,et al.  Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems , 1998, JACM.

[8]  Jens Vygen,et al.  The Book Review Column1 , 2020, SIGACT News.

[9]  Bernhard Korte,et al.  Combinatorial Optimization , 1992, NATO ASI Series.

[10]  Robert E. Tarjan,et al.  Amortized efficiency of list update and paging rules , 1985, CACM.

[11]  Vangelis Th. Paschos,et al.  Algorithms for the On-Line Quota Traveling Salesman Problem , 2004, Inf. Process. Lett..

[12]  David R. Karger,et al.  Approximation algorithms for orienteering and discounted-reward TSP , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..

[13]  Gerhard J. Woeginger,et al.  Developments from a June 1996 seminar on Online algorithms: the state of the art , 1998 .

[14]  Anna R. Karlin,et al.  Competitive snoopy caching , 1986, 27th Annual Symposium on Foundations of Computer Science (sfcs 1986).

[15]  Leen Stougie,et al.  Algorithms for the On-Line Travelling Salesman1 , 2001, Algorithmica.

[16]  Patrick Jaillet,et al.  Probabilistic Traveling Salesman Problems , 1985 .

[17]  Allan Borodin,et al.  Online computation and competitive analysis , 1998 .

[18]  Leen Stougie,et al.  News from the online traveling repairman , 2003, Theor. Comput. Sci..

[19]  Eugene L. Lawler,et al.  Traveling Salesman Problem , 2016 .

[20]  Sanjeev Arora,et al.  Polynomial time approximation schemes for Euclidean TSP and other geometric problems , 1996, Proceedings of 37th Conference on Foundations of Computer Science.

[21]  Leen Stougie,et al.  The Online-TSP against Fair Adversaries , 2000, CIAC.

[22]  Bala Kalyanasundaram,et al.  Constructing Competitive Tours from Local Information , 1993, Theor. Comput. Sci..

[23]  David B. Shmoys,et al.  Scheduling to Minimize Average Completion Time: Off-Line and On-Line Approximation Algorithms , 1997, Math. Oper. Res..

[24]  M Maarten Lipmann,et al.  On-line routing , 2003 .