Semi‐labeled unrooted binary tree optimization subject to nonnegativity

Let Dn×n denote the distance matrix of n objects, and let T be an unrooted binary tree in which the leaves denote those n objects. We want to find such a tree with the constraint that the edge weights are nonnegative where the distances between the leaves best estimate their corresponding values in...

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Published inNetworks Vol. 80; no. 2; pp. 249 - 263
Main Authors Hosseini, Seyed Soheil, Wormald, Nick
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.09.2022
Wiley Subscription Services, Inc
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ISSN0028-3045
1097-0037
1097-0037
DOI10.1002/net.22090

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Summary:Let Dn×n denote the distance matrix of n objects, and let T be an unrooted binary tree in which the leaves denote those n objects. We want to find such a tree with the constraint that the edge weights are nonnegative where the distances between the leaves best estimate their corresponding values in D. Accordingly, we have adopted the residual sum of squares (RSS) criterion to minimize the discrepancy between the distance between leaves in the tree and their corresponding distance in D. For this optimization problem, we have designed an iterated local search (ILS) scheme based on the nearest neighbor interchange (NNI) operation to search the neighborhood.
Bibliography:Funding information
Postgraduate Publication Award (PPA) from the Faculty of Science of Monash University
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ISSN:0028-3045
1097-0037
1097-0037
DOI:10.1002/net.22090