| dc.description.abstract | Construction industry related projects nowadays are mostly managed by site managers and on-site engineers, while relevant work progress and manpower allocation are arranged based on experience as well as available on-site resources and engineering demands. Work assignments are therefore dependent on the experience and capability of the site manager and on-site engineers, which in turn affects the resulting earnings of the project. This study takes the example of a slope foundation excavation project in Taoyuan, Taiwan, carried out via the usual earth excavation work that combines excavators and dump trucks, where basic considerations include (1) minimum costs; (2) the capacity and costs of excavators and trucks; (3) the possibility of finding a shorter construction period; and (4) the maximum number of machines on each site. This study aims to find the most cost effective method for assigning work to each type of machines.
This study constructs a corresponding integer programming model by considering factors of the project such as the number of days of the construction period, work rate and cost of each machine, machine number limits, and progress incentives and punishments. Calculation software is used in combination with word processing software that facilitates the checking of parameter settings to verify the results. This setup allows obtaining more precise results within a short period of time compared to manual scheduling. When external factors and conditions change, this configuration also allows timely adjustment to the newest parameters to carry out the scheduling, so that excavators and dump trucks are assigned according to actual conditions, helping the decision maker of the worksite to use a unified allocation plan for construction machines. This study takes excavation scheduling as an example to configure the model for resolving minimal costs. The results are compared with those made by manual decision making, which shows that the results of this study are better than those made by manual scheduling. Sensitivity analysis is then carried out to check the results obtained by different sensitivities, proving that this study model is actually applicable. | en_US |