A Multi-Objective Memetic Algorithm Based on Chaos Optimization


In this research, a new Memetic Algorithm (MA) for Multi-Objective (MO) optimization is proposed, which combines ability of chaos optimization algorithm is proposed based on the ergodic and stochastic properties of the chaos variables. A new MA updating strategy is proposed based upon the concept to deal with the problem of premature convergence and diversity maintenance within the chromosome. The proposed features are examined to show effects in MO optimization. The comparative study shows the effectiveness of the proposed MA, which produces solution sets that are highly competitive in terms of convergence Measurement and Spread Measurement.