Using SVM to combine global heuristics for the Standard Quadratic Problem-Reference-Cited by-同舟云学术

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Using SVM to combine global heuristics for the Standard Quadratic Problem

Published:2015-03 Issue:3 Volume:241 Page:596-605
ISSN:0377-2217
Container-title:European Journal of Operational Research
language:en
Short-container-title:European Journal of Operational Research

Author:

Dellepiane Umberto,Palagi Laura

Publisher

Elsevier BV

Subject

Information Systems and Management,Management Science and Operations Research,Modelling and Simulation,General Computer Science,Industrial and Manufacturing Engineering

Reference20 articles.

1. Pattern recognition and machine learning;Bishop,2006

2. Evolution towards the maximum clique;Bomze;Journal of Global Optimization,1997

3. On standard quadratic optimization problems;Bomze;Journal of Global Optimization,1998

4. Standard quadratic optimization problems: Algorithms – applications – theory;Bomze,2009

5. Bomze, I., Budinich, M., Pardalos, P. Pelillo, M. ( 1999). The maximum clique problem. Handbook of combinatorial optimization (Vol. A, pp. 1–74). Kluwer Academic Publishers.

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1. New Algorithms and Technologies for Data Mining;Data Mining and Machine Learning Applications;2022-01-28

2. A study on sequential minimal optimization methods for standard quadratic problems;4OR;2021-11-11

3. A hybrid machine-learning and optimization method to solve bi-level problems;Expert Systems with Applications;2018-04

4. Optimization approaches to Supervised Classification;European Journal of Operational Research;2017-09

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