Task Scheduling Algorithm for Warehouse Robots Incorporating Multi-Strategy Optimized SSA
Aiming at the problem of unreasonable robot task assignment in the storage task scheduling process,which leads to the increase of time and path cost of system operation,the task assignment algorithm of multi-strategy optimized sparrow search algorithm is proposed.Firstly,a clone selection mechanism is in-troduced to optimize the initial population and improve the quality of the initial sparrow population;second-ly,an adaptive butterfly update mechanism is designed to replace the discoverer position update method to expand the population search range and balance the global search capability;finally,a backward learning strategy incorporating the probability of variation is introduced to solve the problem of the algorithm falling into local optimum at a later stage.Through several experiments,the algorithm proposed in this paper has significant effect in improving the performance of multi-robot scheduling system.
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