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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

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.

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