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D. Savin, S. Alkass, P. Fazio, "Formulation of the Weight-Matrix of a Neural Network for Resource Leveling", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 95-100, 1995. doi:10.4203/ccp.34.5.2

Abstract

In this paper, a new approach for the computation of the weight-matrix of a neural network (NN) for resource leveling (RL) is introduced. The proposed method achieves significantly improved efficiency over the conventional technique of employing the functional expressions of the weights, by exploiting the structural properties of the matrices arising in the formulation of the RL problem as a quadratic zero-one optimization. These structural properties are identified, and stated in terms of template-matrix contributions of the cost- and constraint-functions of the quadratic optimization, to the weight-matrix of the NN. It is shown that by using these templates, the weight-matrix can be filled-in directly, based on the early start schedule of a project.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 34 DEVELOPMENTS IN NEURAL NETWORKS AND EVOLUTIONARY COMPUTING FOR CIVIL AND STRUCTURAL ENGINEERING Edited by: B.H.V. Topping Paper V.2 Formulation of the Weight-Matrix of a Neural Network for Resource Leveling D. Savin, S. Alkass and P. Fazio Centre for Building Studies, Concordia University, Montreal, Canada doi:10.4203/ccp.34.5.2 purchase the full-text of this paper Full Bibliographic Reference for this paper D. Savin, S. Alkass, P. Fazio, "Formulation of the Weight-Matrix of a Neural Network for Resource Leveling", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 95-100, 1995. doi:10.4203/ccp.34.5.2 Abstract In this paper, a new approach for the computation of the weight-matrix of a neural network (NN) for resource leveling (RL) is introduced. The proposed method achieves significantly improved efficiency over the conventional technique of employing the functional expressions of the weights, by exploiting the structural properties of the matrices arising in the formulation of the RL problem as a quadratic zero-one optimization. These structural properties are identified, and stated in terms of template-matrix contributions of the cost- and constraint-functions of the quadratic optimization, to the weight-matrix of the NN. It is shown that by using these templates, the weight-matrix can be filled-in directly, based on the early start schedule of a project. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £55 +P&P)
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