Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/128131
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Type: Conference paper
Title: Optimising tours for the weighted traveling salesperson problem and the traveling thief problem: a structural comparison of solutions
Author: Bossek, J.
Neumann, A.
Neumann, F.
Citation: Lecture Notes in Artificial Intelligence, 2020 / Bäck, T., Preuss, M., Deutz, A.H., Wang, H., Doerr, C., Emmerich, M.T.M., Trautmann, H. (ed./s), vol.12269, pp.346-359
Publisher: Springer Nature
Publisher Place: Switzerland
Issue Date: 2020
Series/Report no.: Lecture Notes in Computer Science; 12269
ISBN: 9783030581114
ISSN: 0302-9743
1611-3349
Conference Name: International Conference on Parallel Problem Solving from Nature (PPSN) (5 Sep 2020 - 9 Sep 2020 : Leiden, The Netherlands)
Editor: Bäck, T.
Preuss, M.
Deutz, A.H.
Wang, H.
Doerr, C.
Emmerich, M.T.M.
Trautmann, H.
Statement of
Responsibility: 
Jakob Bossek, Aneta Neumann, and Frank Neumann
Abstract: The Traveling Salesperson Problem (TSP) is one of the bestknown combinatorial optimisation problems. However, many real-world problems are composed of several interacting components. The Traveling Thief Problem (TTP) addresses such interactions by combining two combinatorial optimisation problems, namely the TSP and the Knapsack Problem (KP). Recently, a new problem called the node weight dependent Traveling Salesperson Problem (W-TSP) has been introduced where nodes have weights that influence the cost of the tour. In this paper, we compare W-TSP and TTP. We investigate the structure of the optimised tours for W-TSP and TTP and the impact of using each others fitness function. Our experimental results suggest (1) that the W-TSP often can be solved better using the TTP fitness function and (2) final W-TSP and TTP solutions show different distributions when compared with optimal TSP or weighted greedy solutions.
Keywords: Evolutionary algorithms; Traveling Thief Problem; Node weight dependent TSP
Rights: © Springer Nature Switzerland AG 2020
DOI: 10.1007/978-3-030-58112-1_24
Grant ID: http://purl.org/au-research/grants/arc/DP160102401
http://purl.org/au-research/grants/arc/DP190103894
Published version: https://link.springer.com/book/10.1007/978-3-030-58112-1
Appears in Collections:Aurora harvest 8
Computer Science publications

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