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Type: Conference paper
Title: On the impact of local search operators and variable neighbourhood search for the generalized travelling salesperson problem
Author: Pourhassan, M.
Neumann, F.
Citation: Proceedings of the 2015 Genetic and Evolutionary Computation Conference, 2015 / Silva, S. (ed./s), pp.465-472
Publisher: Assocation for Computing Machinery
Issue Date: 2015
ISBN: 9781450334723
Conference Name: 2015 Genetic and Evolutionary Computation Conference (GECCO 2015) (11 Jul 2015 - 15 Jul 2015 : Madrid, Spain)
Statement of
Mojgan Pourhassan, Frank Neumann
Abstract: The generalized travelling salesperson problem is an important NP-hard combinatorial optimization problem where local search approaches have been very successful. We investigate the two hierarchical approaches of Hu and Raidl [9] for solving this problem from a theoretical perspective. We examine the complementary abilities of the two approaches caused by their neighbourhood structures and the advantage of combining them into variable neighbourhood search. We first point out complementary abilities of the two approaches by presenting instances where they mutually outperform each other. Afterwards, we introduce an instance which is hard for both approaches, but where a variable neighbourhood search combining them finds the optimal solution in polynomial time.
Keywords: Generalized travelling salesperson problem, local search, variable neighbourhood search, 2-OPT, combinatorial optimisation
Rights: © 2015 ACM. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from
RMID: 0030042088
DOI: 10.1145/2739480.2754656
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Appears in Collections:Computer Science publications

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