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ParadisEO-MOEO: A software framework for evolutionary multi-objective optimization. (English) Zbl 1189.90143
Coello Coello, Carlos A. (ed.) et al., Advances in multi-objective nature inspired computing. Berlin: Springer (ISBN 978-3-642-11217-1/hbk; 978-3-642-11218-8/ebook). Studies in Computational Intelligence 272, 87-117 (2010).
Summary: This chapter presents ParadisEO-MOEO, a white-box object-oriented software framework dedicated to the flexible design of metaheuristics for multi-objective 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 efficient programs. It is based on a clear conceptual distinction between the solution methods and the problems they are intended to solve. This separation confers a maximum design and code reuse. This general-purpose framework provides a broad range of fitness assignment strategies, the most common diversity preservation mechanisms, some elitistrelated features as well as statistical tools. Furthermore, a number of state-of-the-art search methods, including NSGA-II, SPEA2 and IBEA, have been implemented in a user-friendly way, based on the fine-grained ParadisEO-MOEO components.
For the entire collection see [Zbl 1183.90006].

90C29 Multi-objective and goal programming
90C59 Approximation methods and heuristics in mathematical programming
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