Neural Networks for Combinatorial Optimization: A Review of More Than a Decade of Research
- 1 February 1999
- journal article
- review article
- Published by Institute for Operations Research and the Management Sciences (INFORMS) in INFORMS Journal on Computing
- Vol. 11 (1) , 15-34
- https://doi.org/10.1287/ijoc.11.1.15
Abstract
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.Keywords
This publication has 151 references indexed in Scilit:
- A hybrid approach to sequencing jobs using heuristic rules and neural networksProduction Planning & Control, 1995
- Chaotic simulated annealing by a neural network model with transient chaosNeural Networks, 1995
- Neural methods for the traveling salesman problem: Insights from operations researchNeural Networks, 1994
- Genetic neuro-scheduler for job shop schedulingComputers & Industrial Engineering, 1993
- Asymmetric mean-field neural networks for multiprocessor schedulingNeural Networks, 1992
- Solving inequality constrained combinatorial optimization problems by the hopfield neural networksNeural Networks, 1992
- Applications of counterpropagation networksNeural Networks, 1988
- Self-organizing feature maps and the travelling salesman problemNeural Networks, 1988
- Self-organized formation of topologically correct feature mapsBiological Cybernetics, 1982
- A note on two problems in connexion with graphsNumerische Mathematik, 1959