WIT Press

On The Estimation Of Initial Conditions Of A Neural Network For Resource Leveling

Price

Free (open access)

Paper DOI

10.2495/AI960151

Volume

16

Pages

15

Published

1996

Size

172 kb

Author(s)

D. Savin & S.T. Alkass

Abstract

A procedure for estimating the Lagrange multipliers, suitable for a neural network (NN) model for construction resource leveling (RL), is presented. The procedure uses a modi ed variable-reduction technique, in conjunction with some helpful suggestions on how to choose the initial values of the Lagrange multipliers. The model has been previously developed by mapping a formulation of the RL problem as an augmented Lagrangian multiplier (ALM) optimization, onto an arti cial neural network (ANN) architecture, employing a Hop eld-con guration of NN. In order to ensure the convergence of the NN model, a good estimate of the initial values of the Lagrange multipliers is needed. First, a non-singular decomposition of the constraint matrix is constructed, by taking into account at l

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