Optimal scheduling approach of storage/retrieval equipments based on genetic algorithm

In conventional automated warehouse, the storage and retrieval system is a distributed control system, and the storage/retrieval machines are controlled by traditional control strategy. However, this control mode has some deficiencies: difficult to control accurately the operating status of storage/ retrieval equipments, long operating period and erroneous transferred information. It results in the disability to complete the operation in specified time. The purpose of this paper is to present a new optimal scheduling approach based on genetic algorithm. It considers comprehensively the factors such as work amount, current equipments' status, distance from equipments to storage locations and prediction error probability, which influence the equipments' operation. The study includes the design of code, fitness function, selection operator, crossover operator and mutation operator. Computer simulations show that the method can enable the equipments to realize the pickup and deposit by the shortest route in the shortest time, reducing considerably the operating time.