A Review: Machine Learning for Combinatorial Optimization Problems in Energy Areas

Combinatorial optimization problems (COPs) are a class of NP-hard problems with great practical significance. Traditional approaches for COPs suffer from high computational time and reliance on expert knowledge, and machine learning (ML) methods, as powerful tools have been used to overcome these pr...

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Bibliographic Details
Published in:	Algorithms Vol. 15; no. 6; p. 205
Main Authors:	Yang, Xinyi, Wang, Ziyi, Zhang, Hengxi, Ma, Nan, Yang, Ning, Liu, Hualin, Zhang, Haifeng, Yang, Lei
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.06.2022
Subjects:	Analysis Artificial intelligence China Combinatorial analysis combinatorial optimization problem Competition Computing time Crude oil Decision making Deep learning Electric power systems Energy Game theory Germany Interdisciplinary aspects Machine learning Manufacturing Optimization Pipelines Police refinery scheduling reinforcement learning Scheduling Steel making supervised learning Supply chains Traveling salesman problem Wind power China Germany
ISSN:	1999-4893, 1999-4893
Online Access:	Get full text
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