A Scheduling Optimization Algorithm based on Graph Theory and Simulated Annealing

This paper analyzes the current situation and limitations of scheduling, where it combines the vertex coloring theory of graph theory to form the initial scheduling table; marks the dynamic edges according to the conflict rules; uses the node subtree pruning shortest path method; the simulated annealing algorithm to solve the problem of scheduling conflict so as to balance the complexity associated with time and rationality of personnel arrangement in order to achieve an automated scheduling. The proposed methodology uses the data mining and intelligent model to construct the efficient approach. The experiment results have proven the overall effectiveness.