Exploring the Efficacy of Intelligent Water Drops Algorithm for Solving Nondeterministic Polynomial Problems

Swarm-based optimization algorithms (SBOAs) have demonstrated effectiveness in solving complex problems within a reasonable time. Among these algorithms, the intelligent water drops algorithm (IWD) has recently gained attention for its ability to provide acceptable solutions to difficult problems. The aim of this research is to evaluate the efficiency of the IWD algorithm in addressing the graph coloring problem (GCP), which is a problem that is notoriously difficult to solve and falls under the category of nondeterministic polynomial (NP) hard problems. The algorithm uses multiple drops and cycles to improve solution quality. Experiments show the presented algorithm outperforms the genetic algorithm with multipoint guided mutation for graph coloring (GAMGMGC) and ant-based algorithm for coloring graphs (ABAC) in terms of execution time. Findings advocate additional research on the use of SBOAs, particularly the IWD algorithm, for solving other (NP) hard problems