This paper summarizes a mathematical model that relates the geometric and geotechnical features of a road construction site with the allocation of materials, searching for a minimum construction cost. This paper proposes a linear programming model to optimize excavation and paving services. With this model, it is possible to evaluate site alternatives with different soil strata and different degrees of compaction. The borrow pit materials are allocated in the most economical way, and it is possible to incorporate more inputs like materials mix. Software was used to solve the model, and a spreadsheet application was used as an interface for data input. The proposed model demonstrated possible cost savings in earthwork planning. It is expected that earthwork and paving optimization with linear programming will reduce road construction costs considerably.
The purpose of this paper is to present an optimization model for planning the distribution of materials in earthmoving operations, considering possible interferences between cut-and-fill sections such as rivers, vegetation, topographical features, or expropriations. The earth allocation problem incorporating interferences was modeled as a linear programming problem, aiming to minimize the total earthmoving cost while considering the constraints related to volume balance, construction project duration, and time for the release of traffic. The proposed linear programming model was run by an integrated system, using Excel for data analysis and IBM CPLEX as the optimizer. The mathematical model was evaluated by a sensitivity analysis and validated by a real-world project of a dam access road in the state of Ceará, Brazil. The unit costs and productivity rates used in the fictional example and in the real-world application followed the referential cost system created by Ceará’s Secretariat of Infrastructure (SEINFRA-CE). The proposed optimization model achieved reasonable processing times for all tested applications, presenting itself as a viable and efficient option for planning earthmoving operations. Furthermore, the linear programming approach provided a 2.12% cost reduction for the real-world case study, when comparing the optimized solution and original budget. This study explored the problem of earth allocation with interferences using a linear programming approach, while avoiding complex modeling issues found in recent literature. As a result, this paper proposes a user-friendly optimization system that can be easily utilized by construction companies and departments.
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