Information Technology has enabled new levels of convenience to our daily life. While providing
people with astonishingly good experiences, computer science has still a long way to meet the needs
from the users for various scenarios. As a good example, path selection problem is an important and
common problem which finds applications in location based services, internet routing and
navigation systems. Choosing the most cost effective and time saving routines plays an essential
role in both theory and engineering. Although a plethora of classical solutions have been made to the
static shortest path problem, dynamic shortest path problem has not been thoroughly studied. To
address this critical issue, this paper investigates the dynamic shortest path problem by optimizing
existing work and conducting extensive experiments. The studies fall into three main variants of the
problem: unweighted shortest paths, weighted shortest paths, and shortest paths on the map. We
present a comprehensive comparison of our optimizations and existing solutions which
demonstrates the effectiveness and efficiency of our algorithms.