LAUSR

In this paper, an integrated supply chain management model that draws upon information from radio frequency identification (RFID) and global positioning systems (GPS) is presented. The model automates and optimizes the logistics tasks of grouping, routing, and scheduling. Optimization algorithms are proposed that minimize resource consumption and the traveling time for routes and schedules. Data from RFID readers and GPS units provide instant and dynamic information about the current processing and location status of the logistics jobs. The optimized routes and schedules are then dynamically updated and visualized so that centralized logistics planners can adjust as necessary. The proposed approach thereby combines both discrete and continuous information to assist logistics routings and scheduling to enhance supply chain management. The model can thus tackle the practical problem of variance in processing time, and to identify the segments of a route or schedule for which the processing time varies.