Multi-objective chaos game optimization

Abstract The Chaos Game Optimization (CGO) has only recently gained popularity, but its effective searching capabilities have a lot of potential for addressing single-objective optimization issues. Despite advantages, this method can tackle problems formulated with one objective. multi-objective CGO proposed in study is utilized to handle the several objectives (MOCGO). In MOCGO, Pareto-optimal solutions are stored fixed-sized external archive. addition, leader selection functionality needed carry out been included CGO. technique also applied eight real-world engineering design challenges multiple objectives. MOCGO algorithm uses mathematical models chaos theory and fractals inherited from This algorithm's performance evaluated using seventeen case studies, such as CEC-09, ZDT, DTLZ. Six well-known algorithms compared four different metrics. results demonstrate that suggested better than existing ones. These show excellent convergence coverage.