Many real-world problems involve simultaneous optimization of multiple objectives that often are competing. In such problems, the objectives to be optimized are normally in conflict with respect to each other, which means that there is no single solution for these problems and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. So the solution to this problem is to find a set of solutions , each of which satisfies the objectives at an acceptable level without being affected by any other solution. This review paper presents an overview of multi-objective optimization using GA and PSO.

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GA (Genetic Algorithm) PSO (Particle Swarm Optimization)