A neural network algorithm for the traveling salesman problem with backhauls
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
Hopfield neural networks for timetabling: formulations, methods, and comparative results
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
Meta-heuristics: The State of the Art
ECAI '00 Proceedings of the Workshop on Local Search for Planning and Scheduling-Revised Papers
An Effective Traveling Salesman Problem Solver Based on Self-Organizing Map
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Continuous Function Optimisation via Gradient Descent on a Neural Network Approximation Function
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Fast Winner-Takes-All Networks for the Maximum Clique Problem
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
Automorphism Partitioning with Neural Networks
Neural Processing Letters
Mathematics and Computers in Simulation
Optimizing neural networks on SIMD parallel computers
Parallel Computing
Self-organizing feature maps for the vehicle routing problem with backhauls
Journal of Scheduling
Machine Graphics & Vision International Journal
Computers and Industrial Engineering
Dynamical Systems for Discovering Protein Complexes and Functional Modules from Biological Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A review on evolution of production scheduling with neural networks
Computers and Industrial Engineering
Hopfield Network as Static Optimizer: Learning the Weights and Eliminating the Guesswork
Neural Processing Letters
Binary Optimization: On the Probability of a Local Minimum Detection in Random Search
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
A Neuro-Immune Algorithm to Solve the Capacitated Vehicle Routing Problem
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Letters: A TCNN filter algorithm to maximum clique problem
Neurocomputing
Information Sciences: an International Journal
Neuro-immune approach to solve routing problems
Neurocomputing
Multi-start Stochastic Competitive Hopfield Neural Network for p-Median Problem
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
A Hopfield Network for the Portfolio Selection Problem
Proceedings of the 2005 conference on Artificial Intelligence Research and Development
A neural network approach to multiobjective and multilevel programming problems
Computers & Mathematics with Applications
Prediction of area and length complexity measures for binary decision diagrams
Expert Systems with Applications: An International Journal
A hybrid systematic design for multiobjective market problems: a case study in crude oil markets
Engineering Applications of Artificial Intelligence
A scatter search algorithm for solving vehicle routing problem with loading cost
Expert Systems with Applications: An International Journal
A competitive neural network based on dipoles
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
A gradient network for vector quantization and its image compression applications
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
On conditions for intermittent search in self-organizing neural networks
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
An initiative for a classified bibliography on G-networks
Performance Evaluation
A new Lagrangian net algorithm for solving max-bisection problems
Journal of Computational and Applied Mathematics
Eigenvalue problem approach to discrete minimization
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Minimizing makespan on identical parallel machines using neural networks
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Optical Memory and Neural Networks
Information Sciences: an International Journal
PaCT'11 Proceedings of the 11th international conference on Parallel computing technologies
Critical temperatures for intermittent search in self-organizing neural networks
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
An improved multi-agent approach for solving large traveling salesman problem
PRIMA'06 Proceedings of the 9th Pacific Rim international conference on Agent Computing and Multi-Agent Systems
A coupled gradient network approach for the multi machine earliness and tardiness scheduling problem
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part IV
Engineering Applications of Artificial Intelligence
Bluetooth aided mobile phone localization: A nonlinear neural circuit approach
ACM Transactions on Embedded Computing Systems (TECS)
Mapping parallel programs onto multicore computer systems by Hopfield networks
Optical Memory and Neural Networks
Hi-index | 0.00 |
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 are developed and (sometimes years later) their limitations are realized. This article briefly summarizes the work that has been done and presents the current standing of neural networks for combinatorial optimization by considering each of the major classes of combinatorial optimization problems. Areas which have not yet been studied are identified for future research.