Optimizing Earthmoving Job Planning Based on Evaluation of Temporary Haul Road Networks Design for Mass Earthworks ProjectsSource: Journal of Construction Engineering and Management:;2015:;Volume ( 141 ):;issue: 003DOI: 10.1061/(ASCE)CO.1943-7862.0000940Publisher: American Society of Civil Engineers
Abstract: As a critical component of planning mass earthworks projects, designing effective haul road networks is conducive to delivering the project on time and under budget. The research reported in this paper proposes a grid-based temporary road network design method applicable to a site for which grading design has been completed. Further adding to the existing body of knowledge, a quantitative methodology is proposed for optimizing the detailed planning of earthmoving jobs based on a particular temporary haul road network design. Each job is defined in terms of the source cell, the destination cell, the earth volume, and the shortest-hauling-time path between source and destination. Through seamless integration of the Floyd-Warshall algorithm and linear programming model, the shortest average haul time for a truckload can be obtained while automatically fulfilling site grading design specifications. Based on the resulting average haul time, cost equations are defined to account for (1) the direct truck-hauling crew cost; and (2) building, maintenance, and removal costs of temporary haul roads. As such, the cost associated with executing the optimized earthmoving job plan over a particular haul road network design can be readily assessed, making it straightforward for project managers to compare alternatives. The proposed methodology is demonstrated in steps using a numerical example and further applied in a case study based on a real-world project in northern Alberta.
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contributor author | Chang Liu | |
contributor author | Ming Lu | |
date accessioned | 2017-05-08T22:21:07Z | |
date available | 2017-05-08T22:21:07Z | |
date copyright | March 2015 | |
date issued | 2015 | |
identifier other | 42874683.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/78417 | |
description abstract | As a critical component of planning mass earthworks projects, designing effective haul road networks is conducive to delivering the project on time and under budget. The research reported in this paper proposes a grid-based temporary road network design method applicable to a site for which grading design has been completed. Further adding to the existing body of knowledge, a quantitative methodology is proposed for optimizing the detailed planning of earthmoving jobs based on a particular temporary haul road network design. Each job is defined in terms of the source cell, the destination cell, the earth volume, and the shortest-hauling-time path between source and destination. Through seamless integration of the Floyd-Warshall algorithm and linear programming model, the shortest average haul time for a truckload can be obtained while automatically fulfilling site grading design specifications. Based on the resulting average haul time, cost equations are defined to account for (1) the direct truck-hauling crew cost; and (2) building, maintenance, and removal costs of temporary haul roads. As such, the cost associated with executing the optimized earthmoving job plan over a particular haul road network design can be readily assessed, making it straightforward for project managers to compare alternatives. The proposed methodology is demonstrated in steps using a numerical example and further applied in a case study based on a real-world project in northern Alberta. | |
publisher | American Society of Civil Engineers | |
title | Optimizing Earthmoving Job Planning Based on Evaluation of Temporary Haul Road Networks Design for Mass Earthworks Projects | |
type | Journal Paper | |
journal volume | 141 | |
journal issue | 3 | |
journal title | Journal of Construction Engineering and Management | |
identifier doi | 10.1061/(ASCE)CO.1943-7862.0000940 | |
tree | Journal of Construction Engineering and Management:;2015:;Volume ( 141 ):;issue: 003 | |
contenttype | Fulltext |