In considering distributed adaptive routing schemes for large networks with dynamic topology[ll, the need of an unconventional shortest path algorithm arises from the excessive computation overhead associated with repeated path/distance calculations. This paper provides the design specifics of such an algorithm[2][31, and establishes its performance characteristics through rigorous analysis and simulation. The new algorithm exploits the intrinsic parallelism of neural network architectures and solves the single-pair shortest path problem in such a way that i) the computation time is independent of the number of network nodes, and ii) the frequent shortest distance/path re-calculations inherently associated with topology changes are performed much faster than conventional algorithms. Simple exploitation of the inherent parallelism further allows us to extend the algorithm to solving single-source and all-pair shortest path problems withour compromising the trait of constant convergent complexity.
In the order picking process of the warehouse center, considering the rapid increase in the volume of orders arriving at the picking center at the time of the promotional festival, a hybrid operation mode with multiple picking tables is used to meet the picking requirements of the huge number of real-time orders. Therefore, in this paper, a hybrid picking mode is proposed, taking into account both the idle degree of picking stations and their order item centers of gravity, and a new reinforcement learning algorithm embedding mechanism (PRL) with placeholder control is designed to solve the problem of a huge number of real-time item orders arriving at the picking center system on promotional holidays and in inconsistent quantities, and numerical simulations are performed for this algorithm. The experimental results show that the PRL algorithm in hybrid picking mode can handle a huge number of orders simultaneously and improve picking efficiency effectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.