Code for K-means Optimization Algorithm (KO)

A new metaheuristic optimization algorithm named K-means Optimizer (KO) to solve a wide range of optimization engineering problems

A new metaheuristic optimization algorithm named K-means Optimizer (KO) to solve a wide range of optimization problems from numerical functions to real-design challenges. First, the centroid vectors of clustering regions are established at each iteration using K-means algorithm, then KO proposes two movement strategies to create a balance between the ability of exploitation and exploration. The decision on the movement strategy for exploration or exploitation at each iteration depends on a parameter that will be designed to recognize if each search agent is too long in the region visited with no self-improvement. To demonstrate the effectiveness and reliability of KO, twenty-three classical benchmark functions, CEC2005 and CEC2014 benchmark functions, are employed as a first example and compared with other algorithms. Then, three well-known engineering problems are also considered and their results are compared to the results obtained by the other algorithms.

KO was developed by members of the Center for Engineering Application and Technology Solutions at Ho Chi Minh City Open University, Vietnam.

Link to the published paper: https://doi.org/10.1016/j.knosys.2022.109189