| Summary: | 碩士 === 國立臺灣科技大學 === 營建工程系 === 97 === Ready mixed concrete（RMC）is a kind of famous material in construction engineering from 20 centuries. In general, RMC assignment schedule is controlled by schedule controller’ experience. But, proceeding assignment schedule work by someone’s subjective comment is easy to make some mistake, such as:
a. Most of RMC trucks congregate in a few sites to wait for unloading concrete. It makes traffic chaos and resource idle.
b. Most of sites can’t get RMC trucks. It influences scheduled progress and quality of all engineering.
c. Can’t consider all customers’ orders. It’s hard to supply all orders in a short time.
Such as these views, this research’s topic is” how to calculate a schedule which is shortest and conform all sites’ working time in RMC assignment problem?” This research is also combine Radio Frequency Identification in door management to measure every task real using time. In order to feed back some time factors to optimal system by dynamic element. Hope this system fix these time input data automatically, and then update schedule immediately.
This research applies particle swarm optimization algorithm（PSO）, and update the mathematics model to solve RMC assignment scheduling problem in artificial intelligence（AI）optimal algorithm. Looking forward to use latest algorithm could have faster calculate efficiency, more powerful search ability to get more chance in industrial circles.
This research will establish a system, RFID-Dynamic Assignment Schedule Optimizer system. RFID technology is prompt and hard to pirated. PSO has a lot of advantage like calculate faster, convergence quickly, and search ability more powerful. This system takes advantage of RFID and PSO, feed back schedule information in real time, easy for using interface between user and system, and AI optimal search ability. This research will increase efficiency of RMC trucks assignment work, and apply another new choice to industrial circles.
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