Adaptive hybrid algorithm for dynamic path planning problem of intelligent access system

Dealing with a dynamic routing planning problem of the intelligent access system used in pharmacy, the mathematical formulations were proposed and an hybrid algorithm for this problem was designed. The designed algorithm incorporated the genetic algorithm and particle swarm algorithm and recommended dynamic adjustment and self-adaptive evolution strategies. The previous of the particle algorithm, with dynamic changing of the inertia weight, other parameters also made adjustments to improve search efficiency and search accuracy. In the latter part of the genetic algorithm, with self-adaptive parameter adjustment strategy, the amount of routing information could be maximized according to each iteration, and the search could be driven towards diverse regions of the solution space. The performance of the proposed algorithm was tested on some intelligent access system instances. It proves to be more effective and efficient than other algorithm.