Meta heuristics for the orienteering problem

Yun Chia Liang; Sadan Kulturel-Konak; Alice E. Smith

doi:10.1109/CEC.2002.1006265

Meta heuristics for the orienteering problem

Yun Chia Liang, Sadan Kulturel-Konak, Alice E. Smith

Division of Engineering, Business & Computing (Berks)

Research output: Contribution to conference › Paper › peer-review

37 Scopus citations

Abstract

This paper presents two meta-heuristic techniques, ant colony optimization and tabu search, for the orienteering problem, a general version of the well-known traveling salesman problem with many relevant applications in industry. Both algorithms are compared to other heuristics in the literature. Results on 67 test problems show that the ant colony optimization method and tabu search method perform as well, or better, in all cases and do so at competitive computational cost.

Original language	English (US)
Pages	384-389
Number of pages	6
DOIs	https://doi.org/10.1109/CEC.2002.1006265
State	Published - Jan 1 2002
Event	2002 Congress on Evolutionary Computation, CEC 2002 - Honolulu, HI, United States Duration: May 12 2002 → May 17 2002

Other

Other	2002 Congress on Evolutionary Computation, CEC 2002
Country/Territory	United States
City	Honolulu, HI
Period	5/12/02 → 5/17/02

All Science Journal Classification (ASJC) codes

Software

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10.1109/CEC.2002.1006265

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title = "Meta heuristics for the orienteering problem",

abstract = "This paper presents two meta-heuristic techniques, ant colony optimization and tabu search, for the orienteering problem, a general version of the well-known traveling salesman problem with many relevant applications in industry. Both algorithms are compared to other heuristics in the literature. Results on 67 test problems show that the ant colony optimization method and tabu search method perform as well, or better, in all cases and do so at competitive computational cost.",

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AB - This paper presents two meta-heuristic techniques, ant colony optimization and tabu search, for the orienteering problem, a general version of the well-known traveling salesman problem with many relevant applications in industry. Both algorithms are compared to other heuristics in the literature. Results on 67 test problems show that the ant colony optimization method and tabu search method perform as well, or better, in all cases and do so at competitive computational cost.

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Meta heuristics for the orienteering problem

Abstract

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