关键词: 有轨制导车辆（RGV）, 环形穿梭车调度, 遗传算法, 自适应权重

Abstract: In order to find out the shortest time that traverses all blocks to solve the circular orbit RGV（rail guided vehicles） scheduling problem in automated warehouse, this paper analyzes the main influencing factors and then proposes the goal that find out the shortest path and the least clogging scheme. Mathematical model is established and rule-based Genetic Algorithm is designed to solve the problem. This paper uses adaptive crossover and mutation probability to replace traditional fixed parameters to solve the problem that genetic algorithm is easy to fall into the phenomenon of local optima. An improved dynamic exploring process is advanced for the multi-objective optimization. In the end, the genetic operators are analyzed by experimental comparisons and the algorithm is validated by experiments.

Key words: rail guided vehicles, annular shuttle scheduling, genetic algorithm, dynamic exploring process