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Be the first to like this. No Downloads. Views Total views. Unlike the previous work, our transformation technique transforms a nonlinear equation system into a biobjective optimization problem that can be decomposed into two parts. The advantages of our transformation technique are twofold: 1 all the optimal solutions of a nonlinear equation system are the Pareto optimal solutions of the transformed problem, which are mapped into diverse points in the objective space, and 2 multiobjective evolutionary algorithms can be directly applied to handle the transformed problem.
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In order to verify the effectiveness of our transformation technique, it has been integrated with nondominated sorting genetic algorithm II to solve nonlinear equation systems. The experimental results have demonstrated that, overall, our transformation technique outperforms another state-of-the-art multiobjective optimization based transformation technique and four single-objective optimization based approaches on a set of test instances. The influence of the types of Pareto front on the performance of our transformation technique has been investigated empirically.
Moreover, the limitation of our transformation technique has also been identified and discussed in this paper.
Article :. Aumentar la imagen. I recommend this book to anyone interested in learning about nonlinear multiple objective programming methods, to anyone interested in choosing one of these methods to solve practical problems, and to researchers seeking to create more useful nonlinear multiple objective programming algorithms. All books are shipped in New condition promptly, we are happy to accept returns up to 30 days from purchase.
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Problems with multiple objectives and criteria are generally known as multiple criteria optimization or multiple criteria decision-making MCDM problems.