In view of the problems existing in the automated warehouse

such as many in and out tasks

unbalanced utilization of stacker

great difference in product quality and the impact of task execution process on quality

an emotional bacteria foraging algorithm based on weight strategy and non-uniform elimination diffusion probability distribution is proposed. In order to minimize the running time

equalize the utilization rate of stacker

stabilize the shelf and influence the quality of products

an integrated optimization model is built. In view of the shortcomings of the bacterial foraging algorithm

such as uncertain chemotaxis step length and constant elimination diffusion probability

the Gaussian distribution search mechanism is introduced to update the individual position in the chemotaxis process to avoid the algorithm falling into local optimization

and the emotion is introduced in the mutation process

the weight strategy is introduced to update the individual speed

and the individual emotion perception factor is given to realize the adaptive step size to avoid the premature convergence of the algorithm; around the constancy of probability in the elimination diffusion process

the non-uniform probability distribution is proposed to replace the traditional constant distribution to ensure the population diversity. Simulation and algorithm comparison results show that the proposed algorithm has better performance.