A Commentary on the Progress of Big Data in Combinatorial Optimization

Author:

Cheng Eddie1ORCID,Guo Longkun2,Mao Yaping3,Zhang Xiaoyan4

Affiliation:

1. Department of Mathematics and Statistics, Oakland University, Rochester, Michigan 48309, USA

2. Department of Computer Science, Fuzhou University, Fuzhou, Fujian 350116, PR China

3. School of Mathematics and Statistics, Qinghai Normal University, Xining, Qunghai 810008, PR China

4. School of Mathematical Science & Institute of Mathematics, and Key Laboratory of Ministry of Education Numerical Simulation of Large Scale Complex Systems, Nanjing Normal University, Nanjing, Jiangsu 210023, PR China

Abstract

In this short note, we give remarks regarding big data in combinatorial optimization, with recent progress in this area, as presented in this special issue of Parallel Processing Letters.

Publisher

World Scientific Pub Co Pte Ltd

Reference13 articles.

1. Wiley Encyclopedia of Operations Research and Management Science;Barták R.,2010

2. Machine learning for combinatorial optimization: A methodological tour d’horizon

3. Gröbner Bases and Applications

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