Application of the Crow Search Algorithm for Dynamic Route Optimization

Dynamic route optimization enables frequent updates and optimization of calculated routes while taking into account additional exclusion conditions. In the optimization of tasks related to the issues of dynamic route optimization, algorithms inspired by natural phenomena are widely used. Biologically inspired metaheuristics are characterized by the continuous development of methods based on analogies observed in the functioning of biological life forms. Swarm intelligence approaches, in which the source of the method are the collective behavior of living species occurring in nature, are among the most commonly used algorithms in this category. The aim of this paper is to determine the validity of the CSA algorithm in solving the hypothetical problem of dynamic route optimization.