Robič, Tea; Filipič, Bogdan DEMO: Differential evolution for multiobjective optimization. (English) Zbl 1109.68633 Coello Coello, Carlos A. (ed.) et al., Evolutionary multi-criterion optimization. Third international conference, EMO 2005, Guanajuato, Mexico, March 9–11, 2005. Proceedings. Berlin: Springer (ISBN 3-540-24983-4/pbk). Lecture Notes in Computer Science 3410, 520-533 (2005). Summary: Differential Evolution (DE) is a simple but powerful evolutionary optimization algorithm with many successful applications. In this paper we propose Differential Evolution for Multiobjective Optimization (DEMO) – a new approach to multiobjective optimization based on DE. DEMO combines the advantages of DE with the mechanisms of Pareto-based ranking and crowding distance sorting, used by state-of-the-art evolutionary algorithms for multiobjective optimization. DEMO is implemented in three variants that achieve competitive results on five ZDT test problems.For the entire collection see [Zbl 1069.68002]. Cited in 13 Documents MSC: 68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) 90C29 Multi-objective and goal programming 90C59 Approximation methods and heuristics in mathematical programming Software:SPEA2 PDFBibTeX XMLCite \textit{T. Robič} and \textit{B. Filipič}, Lect. Notes Comput. Sci. 3410, 520--533 (2005; Zbl 1109.68633) Full Text: DOI