Enhancing Recursive Supervised Learning Using Clustering and Combinatorial Optimization (RSL-CC)

2008 ◽  
pp. 157-176
Author(s):  
Kiruthika Ramanathan ◽  
Sheng Uei Guan
Keyword(s):  
Combinatorial Optimization ◽  
Supervised Learning

scholarly journals A Deep Learning Algorithm for the Max-Cut Problem Based on Pointer Network Structure with Supervised Learning and Reinforcement Learning Strategies

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 298 ◽  
Author(s):  
Shenshen Gu ◽  
Yue Yang
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Reinforcement Learning ◽  
Combinatorial Optimization ◽  
Supervised Learning ◽  
Learning Strategies ◽  
Large Scale ◽  
Deep Neural Network ◽  
Max Cut Problem ◽  
Cut Problems

The Max-cut problem is a well-known combinatorial optimization problem, which has many real-world applications. However, the problem has been proven to be non-deterministic polynomial-hard (NP-hard), which means that exact solution algorithms are not suitable for large-scale situations, as it is too time-consuming to obtain a solution. Therefore, designing heuristic algorithms is a promising but challenging direction to effectively solve large-scale Max-cut problems. For this reason, we propose a unique method which combines a pointer network and two deep learning strategies (supervised learning and reinforcement learning) in this paper, in order to address this challenge. A pointer network is a sequence-to-sequence deep neural network, which can extract data features in a purely data-driven way to discover the hidden laws behind data. Combining the characteristics of the Max-cut problem, we designed the input and output mechanisms of the pointer network model, and we used supervised learning and reinforcement learning to train the model to evaluate the model performance. Through experiments, we illustrated that our model can be well applied to solve large-scale Max-cut problems. Our experimental results also revealed that the new method will further encourage broader exploration of deep neural network for large-scale combinatorial optimization problems.

Clustering and combinatorial optimization in recursive supervised learning

2006 ◽  
Vol 13 (2) ◽  
pp. 137-152 ◽  
Author(s):  
Kiruthika Ramanathan ◽  
Sheng Uei Guan
Keyword(s):  
Combinatorial Optimization ◽  
Supervised Learning

Combinatorial Optimization Method Based on Evaluation of Proximate Optimality Using Correlation Coefficient

2015 ◽  
Vol 135 (4) ◽  
pp. 466-467 ◽  
Author(s):  
Masahide Morita ◽  
Hiroki Ochiai ◽  
Kenichi Tamura ◽  
Junichi Tsuchiya ◽  
Keiichiro Yasuda
Keyword(s):  
Combinatorial Optimization ◽  
Correlation Coefficient ◽  
Optimization Method

A Combinatorial Optimization Approach to Solve the Synchronous Optical Network (SONET) Problem

2014 ◽  
Vol 6 (2) ◽  
pp. 9
Author(s):  
Mamoon Alameen ◽  
Mohammad Abdul-Niby ◽  
Tarek Selmi ◽  
Sadeq Damrah
Keyword(s):  
Combinatorial Optimization ◽  
Optical Network ◽  
Optimization Approach

Solution and Investigation of Vector Problems of Combinatorial Optimization on a Set of Polypermutations

2008 ◽  
Vol 40 (12) ◽  
pp. 27-42 ◽  
Author(s):  
Natalya V. Semenova ◽  
Lyudmila N. Kolechkina ◽  
Alla N. Nagornaya
Keyword(s):  
Combinatorial Optimization
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