The central force multi-objective optimization algorithm

In this paper a new method for Multi-Objective Optimization (MOO) has been proposed based on Central Force Optimization algorithm. This method has been called ‘Multi- Objective Central Force Optimization’ algorithm (MOCFO). MOCFO utilizes the concept of ‘Pareto Optimality ’to identify the positions of non-dominated vectors and employs a repository to maintain the positions. The performance of the MOCFO has been evaluated and compared with other optimization techniques which utilize other heuristic algorithms (e.g. particle swarm optimization, and genetic algorithm). The simulation results show that the performance of the proposed MOCFO is comparable to, sometimes better than other MOO techniques. To ensure the true performance of the method presented when opposed with Multi-Objective Optimization Problems, we evaluate it on standard test functions. The final results exhibit the robustness and performance of the so-called method which spans new opportunities of research for the researchers.