A neural network model for scheduling problems
Article Abstract:
An artificial neural network architecture for solving the NP-hard scheduling problems was developed. The architecture, which employs an external processor to 'monitor and control the evolution of the network,' was applied to the single-machine mean tardiness scheduling problem and the minimum makespan job shop scheduling problem. According to test runs, the new procedure is superior to the Wilkerson-Irwin algorithm for the single-machine problem. In addition, it converges to an optimal solution for most job shop scheduling problems.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1996
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A comparison of neural networks and linear scoring models in the credit union environment
Article Abstract:
The performance of feedforward neural networks and traditional statistics-based discriminant analysis methods in constructing credit scoring models using the database of three US credit unions was compared. Specifically, the predictive ability of multilayer perceptrons and modular neural networks was evaluated. The results indicated that customized neural networks are superior only when the performance criteria are a percentage of bad loans correctly classified.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1996
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A new neural network for solving linear programming problems
Article Abstract:
A simple and low-cost analog neural network architecture for solving linear programming (LP) problems is described. The universal and flexible network architecture, which may be easily implemented using very-large-scale-integration technology, is based on nonlinear differential equation representations of LP problems. Its main components are a single neuron, adaptive synaptic weights which are modified by a learning algorithm and a pre-processing circuit.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1996
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