Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
The shifting bottleneck procedure for job shop scheduling
Management Science
Simulated annealing and Boltzmann machines: a stochastic approach to combinatorial optimization and neural computing
Learning and relearning in Boltzmann machines
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
A stochastic neural network for resource constrained scheduling
Computers and Operations Research - Special issue on neural networks and operations research
Multiple job scheduling with artificial neural networks
Computers and Electrical Engineering - Special issue on artificial intelligence in engineering design and manufacturing
Heuristics for scheduling flexible flow lines
Computers and Industrial Engineering
Genetic neuro-scheduler for job shop scheduling
Proceedings of the 15th annual conference on Computers and industrial engineering
Towards designing artificial neural networks by evolution
Applied Mathematics and Computation - Special issue on articficial life and robotics
A neural-net approach to real time flow-shop sequencing
Computers and Industrial Engineering
Scheduling jobs on parallel machines applying neural network and heuristic rules
Computers and Industrial Engineering
Neural network and genetic algorithm-based hybrid approach to expanded job-shop scheduling
Computers and Industrial Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
A new adaptive neural network and heuristics hybrid approach for job-shop scheduling
Computers and Operations Research
Evolutionary Learning of Modular Neural Networks withGenetic Programming
Applied Intelligence
A Neural Network with Evolutionary Neurons
Neural Processing Letters
Preface: focused issue on applied meta-heuristics
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
Neural Networks for Combinatorial Optimization: a Review of More Than a Decade of Research
INFORMS Journal on Computing
Using MLP networks to design a production scheduling system
Computers and Operations Research - Special issue: Emerging economics
Global Optimisation by Evolutionary Algorithms
PAS '97 Proceedings of the 2nd AIZU International Symposium on Parallel Algorithms / Architecture Synthesis
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
An artificial neural network for resource leveling problems
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
A neuro-tabu search heuristic for the flow shop scheduling problem
Computers and Operations Research
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
Scheduling multiprocessor job with resource and timing constraintsusing neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
A theoretical investigation into the performance of the Hopfield model
IEEE Transactions on Neural Networks
A neural network approach to job-shop scheduling
IEEE Transactions on Neural Networks
Computers and Industrial Engineering
An improved constraint satisfaction adaptive neural network for job-shop scheduling
Journal of Scheduling
Training a neural network to select dispatching rules in real time
Computers and Industrial Engineering
Multilayer perceptron for simulation models reduction: Application to a sawmill workshop
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
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The production scheduling problem allocates limited resources to tasks over time and determines the sequence of operations so that the constraints of the system are met and the performance criteria are optimized. One approach to this problem is the use of artificial neural networks (ANNs) stand alone or in conjunction with other methods. Artificial neural networks are computational structures that implement simplified models of biological processes, and are preferred for their robustness, massive parallelism, and learning ability. In this paper, we give a comprehensive overview on ANN approaches for solution of production scheduling problems, discuss both theoretical developments and practical experiences, and identify research trends. More than 50 major production and operations management journals published in years 1988-2005 have been reviewed. Existing approaches are classified into four groups, and additionally a historical progression in this field was emphasized. Finally, recommendations for future research are suggested in this paper.