This study used optimization via ABC-PSO mixed coding to solve problems involving mixed integer nonlinear programming (MINLP) and mixed integer linear programming (MILP). The combination of ABC (Artificial Bee Colony) and PSO (Particle Swarm Optimization) is assessed with reference to seven benchmark problem tests. The A algorithm was then tested and analyzed. The proposed approach is shown to compare favorably with other established meta-heuristic techniques on the basis of the results provided in this study. This study also considers the specific attributes of the ABC-PSO algorithm with a focus on the potential consequences of application for actual constrained optimization.