When a multiobjective optimization problem is tackled using Pareto optima theory, particular care has to be taken to obtain a full sampling of the Pareto Optimal Front. This leads to variability of individuals in both design space and objective space. We compare two different fitness assignment strategies based on two individual sharing procedures in the space domain and in the objective domain on some test cases.
Di Barba, P., Farina, M. and Savini, A. (2001), "An improved technique for enhancing diversity in Pareto evolutionary optimization of electromagnetic devices", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 20 No. 2, pp. 482-496. https://doi.org/10.1108/03321640110383366Download as .RIS
MCB UP Ltd
Copyright © 2001, MCB UP Limited