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N.N. Dawood, "An Evaluation Study of Neural Network and Heuristic Approaches to Construction Resource Planning", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 107-114, 1995. doi:10.4203/ccp.34.5.4

Abstract

The objective of this paper is 10 evaluate and compare the performance of the Neural Networks (NNs) and Heuristic approaches to resource allocation and planning in the construction industry. The NN model, developed by Shimazaki, uses the Hopfield type of NNs. The Heuristic model, developed by the author, is a computer-based resource-constrained simulation model which uses the LST (Latest Start Time) rule for resource allocation. A case study of a small project was used to run the two models and the results schedules were evaluated using a number of criteria. It was concluded that the Heuristic model is more flexible and produced smoother resource profile compared with the NN model. Also, the results obtained from the Heuristic model can be fully justified and verified.

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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.4 An Evaluation Study of Neural Network and Heuristic Approaches to Construction Resource Planning N.N. Dawood Division of Civil Engineering and Building, University of Teesside, Middlesbrough, UK doi:10.4203/ccp.34.5.4 purchase the full-text of this paper Full Bibliographic Reference for this paper N.N. Dawood, "An Evaluation Study of Neural Network and Heuristic Approaches to Construction Resource Planning", in B.H.V. Topping, (Editor), "Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 107-114, 1995. doi:10.4203/ccp.34.5.4 Abstract The objective of this paper is 10 evaluate and compare the performance of the Neural Networks (NNs) and Heuristic approaches to resource allocation and planning in the construction industry. The NN model, developed by Shimazaki, uses the Hopfield type of NNs. The Heuristic model, developed by the author, is a computer-based resource-constrained simulation model which uses the LST (Latest Start Time) rule for resource allocation. A case study of a small project was used to run the two models and the results schedules were evaluated using a number of criteria. It was concluded that the Heuristic model is more flexible and produced smoother resource profile compared with the NN model. Also, the results obtained from the Heuristic model can be fully justified and verified. 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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