End-to-end constrained optimization learning: A survey
This paper surveys the recent attempts at leveraging machine learning to solve constrained
optimization problems. It focuses on surveying the work on integrating combinatorial solvers …
optimization problems. It focuses on surveying the work on integrating combinatorial solvers …
Neural networks for combinatorial optimization: a review of more than a decade of research
KA Smith - Informs journal on Computing, 1999 - pubsonline.informs.org
It has been over a decade since neural networks were first applied to solve combinatorial
optimization problems. During this period, enthusiasm has been erratic as new approaches …
optimization problems. During this period, enthusiasm has been erratic as new approaches …
Neural combinatorial optimization with reinforcement learning
This paper presents a framework to tackle combinatorial optimization problems using neural
networks and reinforcement learning. We focus on the traveling salesman problem (TSP) …
networks and reinforcement learning. We focus on the traveling salesman problem (TSP) …
Exploratory combinatorial optimization with reinforcement learning
Many real-world problems can be reduced to combinatorial optimization on a graph, where
the subset or ordering of vertices that maximize some objective function must be found. With …
the subset or ordering of vertices that maximize some objective function must be found. With …
[LIVRE][B] An introduction to neural networks
K Gurney - 2018 - taylorfrancis.com
Though mathematical ideas underpin the study of neural networks, the author presents the
fundamentals without the full mathematical apparatus. All aspects of the field are tackled …
fundamentals without the full mathematical apparatus. All aspects of the field are tackled …
Deep reinforcement learning for the electric vehicle routing problem with time windows
The past decade has seen a rapid penetration of electric vehicles (EVs) as more and more
logistics and transportation companies start to deploy electric vehicles (EVs) for service …
logistics and transportation companies start to deploy electric vehicles (EVs) for service …
[LIVRE][B] Neural networks: a systematic introduction
R Rojas - 2013 - books.google.com
Neural networks are a computing paradigm that is finding increasing attention among
computer scientists. In this book, theoretical laws and models previously scattered in the …
computer scientists. In this book, theoretical laws and models previously scattered in the …
[LIVRE][B] Introduction to the theory of neural computation
JA Hertz - 2018 - taylorfrancis.com
INTRODUCTION TO THE THEORY OF NEURAL COMPUTATION Page 1 Page 2
INTRODUCTION TO THE THEORY OF NEURAL COMPUTATION Page 3 Page 4 …
INTRODUCTION TO THE THEORY OF NEURAL COMPUTATION Page 3 Page 4 …
[PDF][PDF] On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms
P Moscato - Caltech concurrent computation program, C3P …, 1989 - researchgate.net
Large Numbers\... the optimal tour displayed (see Figure 6) is the possible unique tour
having one arc xed from among 10655 tours that are possible among 318 points and have …
having one arc xed from among 10655 tours that are possible among 318 points and have …
[LIVRE][B] Artificial neural networks
B Yegnanarayana - 2009 - books.google.com
Designed as an introductory level textbook on Artificial Neural Networks at the postgraduate
and senior undergraduate levels in any branch of engineering, this self-contained and well …
and senior undergraduate levels in any branch of engineering, this self-contained and well …