اولویت مبتنی بر الگوریتم ژنتیک برای تعارض- هدایت رایگان مسیریابی خودکار وسیله نقلیه

This study presents an algorithm for automated guided vehicle system routing. Priority-based genetic algorithm was used for genetic representation. The objective is minimal path transverse time. Weight mapping crossover (WMX) and insertion mutation was used as genetic operators. Conflict detection and avoidance was incorporated into the system using node and arc occupation time mapping for detection and replacement of the individual with faultless individual from the population for avoidance. Numerical experimentation was conducted to test the effectiveness of the algorithm.

The current usage of Automated Guided Vehicles (AGVs) to transport material between various FMS cells result in bottleneck arising from ineffectiveness of the routing techniques in use[1]. Each request needs generation of optimal route to the dispatched AGV, as a result of serving different request the AGVs travels on the guide path network simultaneously, shortest distance and collision avoidance must be ensured.