| dc.description.abstract | In recent years, ready mixed concrete (RMC) has became one of the most primary construction material of buildings and other public infrastructures. It is produced by automatic process and computer controlled process, and then delivered by RMC trucks. However, when RMC mixer is breakdown unexpectedly, RMC batch might not satisfy the demand of construction sites. Consequently, the operation cost of both RMC batch and construction sides would be increased. To deal with this situation, the dispatcher would manually adjust the original production scheduling and truck dispatching by experienced staff. It might lead to a result of wasting resources and decreasing the quality of service. Therefore, in this research, we aimed at dealing with the situation when RMC mixer is breakdown unexpectedly. To support the supplying, RMC is supplied by using all the applicable resources of the company in the specific area. By angle of owners of RMC Companies, we considered the operation costs of both RMC batch and construction sides. Besides, we also considered the operation characteristics of this industry. In this research, we systematically constructed two models. We first constructed the real time RMC truck dispatching with single type of trucks. Further, based on the first model, we constructed the real time RMC truck dispatching with various types of trucks. These two models are expected to be useful planning tools for helping dispatchers adjust truck dispatching more effectively, and thus to minimize loss of system profits and to maintain their quality of service.
We applied time-space network techniques with the system optimization perspective to construct two real-time truck dispatching models. These two models are formulated as mixed integer network flow problems with side constraints, which are characterized as NP-hard. To solve realistic problems efficiently, we developed a solution method, which incorporates a mathematical programming solver CPLEX. To solve the problems more efficiently, we used problem decomposition techniques to develop the heuristic to solve the problems. In order to test the models and solution algorithms in actual operations, we performed a case study based on the real operating data from an RMC firm in Taiwan. The test results show that the models and the solution algorithm would be better then actual operations. | en_US |