| Summary: | 碩士 === 國立中央大學 === 土木工程學系碩士在職專班 === 100 === Abstract
The deployment of truck fleet in the moving of residual earth relies mainly on the rule of thumb to decide appropriate vehicle dispatching in the traditional construction industry. If the caseload of contractor increases and the vehicle dispatching is more complex, whether the vehicle dispatching by the decision-makers is appropriate or not become an important issue for contractors. Good deployment can improve efficiency and make more profits. This study proposes a linear optimization model which determines individual vehicle resources required to be assigned by minimizing cost when several earth-removing works need to be processed by the contractor at the same time. This linear optimization model can be a reference for decision-makers.
Besides, based on reviewing the variation trends of sensitivity in each parameter, the sensitivity analysis is able to find a solution with a minimum cost. This optimum allocation can not only improve efficiency but also make full use of vehicles as well as human resource.
There are several basic data need to be tabulated by EXCEL software in the linear optimization process, such as the earth removing quantity for each work, the allowable quantity of dumping soil, working hour limitation and time of transportation. Using the input table from previous step as known data and solved with LINGO 8.0 software package, both a vehicle dispatching solution with minimum cost and the overall required trips for earth-removing can be determined. To verify the rationality and the usability of this mode, a set of customized data were assumed as basic data for several earth-removing works during simulation. The result obtained from this linear optimization model is compared with that obtained from method based on human experience. It is shown that this linear optimization model is more efficient and requires less processing time in comparison with manual allocation method which based mainly on human experience. As a result, the proposed linear optimization model can be flexibly applied to the pre-planning allocation of both human and vehicles resource. Furthermore, vehicle dispatching in the moving of residual earth cab be more effectively by planning with this proposed method.
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