Extensions to the repetitive branch and bound algorithm for globally optimal clusterwise regression

DOI10.1016/j.cor.2012.02.007zbMath1251.90313OpenAlexW1984745425MaRDI QIDQ1761225

Réal A. Carbonneau, Pierre Hansen, Gilles Caporossi

Publication date: 15 November 2012

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2012.02.007

zbMATH Keywords

global optimizationheuristicscombinatorial optimizationbranch and boundsequencingclusterwise regression

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Approximation methods and heuristics in mathematical programming (90C59) Combinatorial optimization (90C27)

Related Items (9)

Globally optimal clusterwise regression by column generation enhanced with heuristics, sequencing and ending subset optimization ⋮ The role of optimization in some recent advances in data-driven decision-making ⋮ Clusterwise support vector linear regression ⋮ Scalable and near-optimal \(\varepsilon\)-tube clusterwise regression ⋮ DC programming algorithm for clusterwise linear \(L_1\) regression ⋮ Incremental DC optimization algorithm for large-scale clusterwise linear regression ⋮ Nonsmooth DC programming approach to clusterwise linear regression: optimality conditions and algorithms ⋮ An algorithm for clusterwise linear regression based on smoothing techniques ⋮ An exact algorithm for the two-mode \(KL\)-means partitioning problem

Uses Software

• AS 75
• CPLEX
• Algorithm 39
• DASL

Cites Work

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• A maximum likelihood methodology for clusterwise linear regression
• Correction to: Algorithm 39. Clusterwise linear regression
• A fast algorithm for clusterwise linear regression
• Clusterwise linear regression
• Identifiability of models for clusterwise linear regression
• A mathematical programming approach to clusterwise regression model and its extensions
• A mixture likelihood approach for generalized linear models
• Mixed logical-linear programming
• A repetitive branch-and-bound procedure for minimum within-cluster sums of squares partitioning
• Logic, Optimization, and Constraint Programming
• Cost-Bounded Binary Decision Diagrams for 0-1 Programming
• A Branch and Bound Clustering Algorithm
• A bio-mimetic approach to marketing segmentation: Principles and comparative analysis
• A dyadic segmentation approach to business partnerships
• Least Squares Computations by Givens Transformations Without Square Roots
• Locally Linear Regression and the Calibration Problem for Micro-Array Analysis

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