Optimization of Earthmoving Operations in Heavy Civil Engineering Projects

Moselhi, Osama; Alshibani, Adel

doi:10.1061/(asce)0733-9364(2009)135:10(948)

Cited by 73 publications

(32 citation statements)

References 14 publications

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“…The studies above are based on a transportation model in a bid to improve the transportation efficiency. The study has been developed to those on a soil hauling method that considers a number of factors (such as worker's resource, budget, indirect cost) based on transportation theory, which further influences road construction [6,7]. The importance of the hauling plan including the dump site/borrow pit failed to be considered in such studies because they only focused on certain influential factors related to road construction [8].…”

Section: Background and Objectivementioning

confidence: 99%

“…Moselhi [6] conducted a study to minimize the earthwork volume and developed the model for decision-making by the worker to effectively carry out the earthwork in a practical way considering various factors that may influence spoil-hauling such as a worker's resource, budget, soil characteristics, indirect cost and equipment characteristics. The model however, has a limit in use for hauling within the site because nonlinear programming which is rather more complex was used instead of linear programming in the process of calculating many factors.…”

Section: Trend Of Related Studiesmentioning

confidence: 99%

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Development of a Prototype Model to Establish an Economic Earthwork Plan that Includes the Selection of a Dump Site/Borrow Pit

Lee¹,

Son

Lee

2017

Sustainability

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Earthwork in road construction projects is the major activity that accounts for about 20%-30% of the total construction cost, and the internal/external hauling plan is the key factor for determining the successful completion of the project. However, the hauling plan at the site, which includes the selection of the dump site and borrow pit, is usually determined by the site manager's subjective and empirical discretion alone. Therefore, this study has developed a prototype model that provides the optimal internal/external hauling plan. It includes the determination of the most economical dump sites and borrow pits (location and number) among other candidate sites as well. The transshipment problem theory is incorporated into the optimized algorithm with the consideration of various factors affecting earthwork cost. Direct costs from an optimized transport based on an existing model against another from this model were compared to prove its feasibility. As a result, the reduction of earthwork cost including the dump site/borrow pits reached 4%-8%. This result implies that this prototype model would also be useful in reducing both the earthwork cost and the occurrence of exhaust gas from earthwork equipment by providing optimized transportation paths.

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Section: Background and Objectivementioning

confidence: 99%

Section: Trend Of Related Studiesmentioning

confidence: 99%

Development of a Prototype Model to Establish an Economic Earthwork Plan that Includes the Selection of a Dump Site/Borrow Pit

Lee¹,

Son

Lee

2017

Sustainability

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“…The model was used for crew optimization during planning and control of earthmoving operations. Furthermore, Moselhi and Alshibani (2009) expanded their initial model and developed a new system that utilizes GAs, linear programming, and GIS. The new model widens the optimization scale of earth-moving operations to accommodate heavy civil engineering projects.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimum Planning for Multi-Project Earthmoving Operations

Abu-Samra¹,

Hakea²,

Khalil³

et al. 2013

Proceedings of the 30th International Symposium on Automation and Robotics in Construction and Mining (ISARC 2013): Building Th

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By virtue of its complex nature, the construction industry comprises a wide spectrum of interrelated variables and factors. This multifaceted character of the construction industry puts the use of engineering modeling tools and techniques on top of project management necessities. This research introduces a macro-level earthmoving management system using Genetic Algorithms (GAs) to reach the optimum allocation of earthmoving equipment. The Earthmoving Equipment Management System (EEMS) functions through four integrated modules: (1) A Central Database containing information about projects and available equipment; (2) An Equipment per Segment Selection module that calculates the cut and fill quantities, plots the Mass Haul Diagrams, and selects the equipment types to be used for each segment; (3) An Equipment Pool module which determines the production and cost for each available equipment, based upon the project site conditions; and (4) An Optimization Engine equipped with a GA optimization solver. This engine formulates the optimum earthmoving cost for all projects, by changing the number of allocated equipment. The Optimization Engine takes into account the number of available equipment and calculates the weekly equipment allocation. The EEMS model was implemented on an earthmoving company conducting five different projects on hand. The model proved to be an effective tool in providing decision makers with optimum equipment utilization on a multi-project scale to minimize the earthmoving cost. The results were then compared with the company's existing micro-level management system, demonstrating better performance on the level of savings, amounting to 13% of total earthmoving cost.

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“…Figure 6 shows excavation work of the project under consideration. A near optimum crew, however, can be obtained using optimization model described earlier by the authors (Alshibani and Moselhi, 2009). The hourly loader and truck cost is $85 and $185, respectively.…”

Section: Application Examplementioning

confidence: 99%

Automated System for Productivity Assessement of Earthmoving Operations

Alshibani¹,

Moselhi²

2010

Proceedings -- The 27th International Symposium on Automation and Robotics in Construction

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Onsite data collection is essential for estimating onsite productivity, measuring project performance, and tracking large earthmoving operations. This paper presents a web-based system, developed for estimating onsite productivity and tracking earthmoving operations. The paper briefly describes the main components of the developed system and focuses primarily on estimating onsite productivity .The proposed system utilizes spatial technologies including GPS and GIS in addition to Google maps to support its management functions. The proposed system is most suited for large earthmoving projects. GPS is used to automate onsite data collection in near real time and to facilitate information exchange among members of project teams. GIS is employed not only to automate data acquisition, but also to analyze collected spatial data. The developed system has been coded in prototype software using object-oriented programming and Microsoft Foundation Classes (MFC). Real case example of a construction project is analyzed to demonstrate the features of the developed model.

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Optimization of Earthmoving Operations in Heavy Civil Engineering Projects

Cited by 73 publications

References 14 publications

Development of a Prototype Model to Establish an Economic Earthwork Plan that Includes the Selection of a Dump Site/Borrow Pit

Development of a Prototype Model to Establish an Economic Earthwork Plan that Includes the Selection of a Dump Site/Borrow Pit

Optimum Planning for Multi-Project Earthmoving Operations

Automated System for Productivity Assessement of Earthmoving Operations

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