Titlebook: Advances in Multi-Objective Nature Inspired Computing; Carlos A. Coello Coello,Clarisse Dhaenens,Laetitia Book 2010 Springer-Verlag Berlin

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Advances in Multi-Objective Nature Inspired Computing

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Advances in Multi-Objective Nature Inspired Computing978-3-642-11218-8Series ISSN 1860-949X Series E-ISSN 1860-9503

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Series in Display Science and Technologye the whole Pareto front efficiently and one is interested in good approximations. We consider how evolutionary algorithms can achieve such an approximation by using different diversity mechanisms. We discuss some well-known approaches such as the density estimator and the . -dominance approach and

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https://doi.org/10.1007/978-3-030-02834-3licity and its fast convergence properties. In the last few years there has been a variety of proposals for extending it to handle with multiples objectives. Although many of them keep the same properties of the original algorithm, they face difficulties when tackling the optimization of some multi-

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Environmental Effects on Color Visiontives that are in conflict. In these dynamic multi-objective problems the concept of optimum must be redefined, because instead of providing only one optimal solution, the procedures applied to these multi-objective optimization problems should obtain a set of non-dominated solutions (known as Paret

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Color Basics for the Display Designerctive optimization. This paradigm-free software proposes a unified view for major evolutionary multi-objective metaheuristics. It embeds some features and techniques for multi-objective resolution and aims to provide a set of classes allowing to ease and speed up the development of computationally e

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Colorimetry of Self-Luminous Displayse criterion search model. This model gives a framework for many well-known evolutionary and local search algorithms. Using the biobjective traveling salesman problem as an example application, we analyse the impact of three important algorithmic components on the performance of a simple local search

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