Approximation Algorithms for the Generalized Team Orienteering Problem and Its Applications

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

2 Scopus Citations
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Author(s)

  • Wenzheng Xu
  • Zichuan Xu
  • Jian Peng
  • Dezhong Peng
  • Tang Liu
  • Sajal K. Das

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)176-189
Journal / PublicationIEEE/ACM Transactions on Networking
Volume29
Issue number1
Online published7 Oct 2020
Publication statusPublished - Feb 2021

Abstract

In this article we study a generalized team orienteering problem (GTOP), which is to find service paths for multiple homogeneous vehicles in a network such that the profit sum of serving the nodes in the paths is maximized, subject to the cost budget of each vehicle. This problem has many potential applications in IoTs and smart cities, such as dispatching energy-constrained mobile chargers to charge as many energy-critical sensors as possible to prolong the network lifetime. In this article, we first formulate the GTOP problem, where each node can be served by different vehicles, and the profit of serving the node is a submodular function of the number of vehicles serving it. We then propose a novel (1-(1/e)1/2+ε)-approximation algorithm for the problem, where ε is a given constant with 0 < ε ≤ 1 and e is the base of the natural logarithm. In particular, the approximation ratio is about 0.33 when ε = 0.5. In addition, we devise an improved approximation algorithm for a special case of the problem where the profit is the same by serving a node once and multiple times. We finally evaluate the proposed algorithms with simulation experiments, and the results of which are very promising. Especially, the profit sums delivered by the proposed algorithms are up to 14% higher than those by existing algorithms, and about 93.6% of the optimal solutions.

Research Area(s)

  • approximation algorithms, Dispatching, Electronic mail, Intelligent sensors, Monitoring, Multiple vehicle scheduling, submodular function, the generalized team orienteering problem

Citation Format(s)

Approximation Algorithms for the Generalized Team Orienteering Problem and Its Applications. / Xu, Wenzheng; Liang, Weifa; Xu, Zichuan; Peng, Jian; Peng, Dezhong; Liu, Tang; Jia, Xiaohua; Das, Sajal K.

In: IEEE/ACM Transactions on Networking, Vol. 29, No. 1, 02.2021, p. 176-189.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review