<?xml version="1.0" encoding="UTF-8"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-10-29T21:49:37Z</responseDate><request verb="GetRecord" identifier="oai:munzur-rdlopen.rawdatalibrary.net:munzur/4339" metadataPrefix="oai_dc">https://munzur-rdlopen.rawdatalibrary.net/oai/request</request><GetRecord><record><header><identifier>oai:munzur-rdlopen.rawdatalibrary.net:munzur/4339</identifier><datestamp>2026-10-28T15:31:29Z</datestamp><setSpec>openaire</setSpec><setSpec>driver</setSpec><setSpec>com_munzur_1</setSpec><setSpec>col_munzur_2</setSpec><setSpec>com_munzur_8</setSpec><setSpec>col_munzur_157</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:title>A Consensus-Edge Initializer for Multi-start 2-opt on the Symmetric Euclidean Travelling Salesman Problem</dc:title><dc:creator>Saygili, Ahmet Caglar</dc:creator><dc:creator>Kazan, Halim</dc:creator><dc:subject>Travelling Salesman Problem</dc:subject><dc:subject>local search</dc:subject><dc:subject>-opt</dc:subject><dc:subject>consensus edges</dc:subject><dc:subject>heuristics</dc:subject><dc:description>We study a one-shot consensus-based initializer for multi-start 2-opt on symmetric Euclidean Travelling Salesman Problem (TSP) instances. Given the M local minima from best-of-M 2-opt, we count undirected edge frequencies, greedily assemble a tour from the most frequent edges with a length-biased tie-break, and run a single additional 2-opt descent from this seed. The local search operator is unchanged; the consensus stage reuses existingtours and adds only a small overhead beyond the M descents, and we characterise this overhead analytically while focusing evaluation on tour length improvements. On synthetic Euclidean instances from three generators, we evaluate performance over a grid of problem sizes n and restart budgets M. The consensus + 2-opt pipeline improves best-of-M 2-opt by roughly 3-6% in median tour length with high win rates for n &gt;= 500 and moderate M, while for small n and large M the baseline saturates and gains shrink to zero or slightly negative values. Thus, even a single aggregation step over 2-opt local minima yields a simple, reproducible seed that is beneficial in the practically relevant regime of moderate budgets and larger instances and approximately neutral elsewhere.</dc:description><dc:publisher>ISTANBUL UNIV</dc:publisher><dc:date>2026</dc:date><dc:type>Article</dc:type><dc:identifier>https://rdlopen.rawdatalibrary.net/r/munzur/4339</dc:identifier><dc:identifier>https://doi.org/10.26650/ekoist.2026.xx.1824864</dc:identifier><dc:identifier>2651-396X</dc:identifier><dc:language>en</dc:language><dc:relation>EKOIST-JOURNAL OF ECONOMETRICS AND STATISTICS</dc:relation><dc:rights>info:eu-repo/semantics/openAccess</dc:rights><dc:type>info:eu-repo/semantics/article</dc:type><dc:identifier>https://munzur-rdlopen.rawdatalibrary.net/tr/items/munzur/4339</dc:identifier></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>