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An expert system to optimize cost and schedule of heavy earthmoving operations for earth- and rock- filled dam projects

    Nizar Markiz Affiliation
    ; Ahmad Jrade Affiliation

Abstract

Success of major embankment dam construction projects is measured by the enormity of optimizing costs and schedules of selected heavy equipment based on their operational analyses. In this paper, the main objective is geared towards developing a knowledge-based decision support system for optimizing costs of heavy earthmoving operations and corresponding linear schedules at early design stages. Also, the proposed system is capable of generating an auto­mated linear schedule based on stochastic scheduling techniques. Thus, a meta-heuristic simulated approach utilizing a metropolis algorithm is implemented to assist in generating optimized line-of balances. The successful implementation of the proposed system will provide the user with optimum fleet of equipment for performing earthwork operations and linear scheduling for strategic planning purposes. Towards the end, an actual dam construction project is utilized to numerically validate the proposed system and quantify its degree of accuracy. Results presented in this study are an­ticipated to be of major significance to owners, designers, and construction managers specialized in embankment dams heavy earthmoving operations and would contribute to the database of fleet management systems by incorporating a novel system that integrates heavy equipment economical operational analyses with its corresponding line of balance.


First published online: 15 Dec 2015

Keyword : decision-support, heavy equipment, operation analysis, cost estimation, linear scheduling

How to Cite
Markiz, N., & Jrade, A. (2017). An expert system to optimize cost and schedule of heavy earthmoving operations for earth- and rock- filled dam projects. Journal of Civil Engineering and Management, 23(2), 222-231. https://doi.org/10.3846/13923730.2015.1027258
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Feb 6, 2017
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This work is licensed under a Creative Commons Attribution 4.0 International License.