Evolutionary Multimodal Optimization
A special issue of Mathematical and Computational Applications (ISSN 2297-8747).
Deadline for manuscript submissions: 15 March 2025 | Viewed by 126
Special Issue Editors
2. Data Management and Biometrics Group, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
Interests: trustworthy artificial intelligence; evolutionary optimization; data science; automated algorithm selection; automated algorithm configuration; data stream mining; social media analytics
Interests: multi-objective optimization (esp. visualization); algorithm selection; data science
Interests: multi-objective optimization; evolutionary computation (genetic algorithms and evolution strategies); numerical analysis; engineering applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the context of optimization, multimodality describes the existence of multiple locally (or globally) optimal solutions. Multimodality is often one of the main challenges associated with optimizing a given problem and, thus, one of the main properties considered when developing optimization algorithms and designing benchmark sets to evaluate and compare state-of-the-art methods. Additionally, decision-makers are often interested in more than one (best) solution to a given optimization problem and want to be offered a variety of good alternative solutions with different characteristics. Sometimes, especially in practical applications, near-optimal solutions with specific properties are considered interesting as well, justifying the need for finding and characterizing locally optimal solutions as well.
The aims of this Special Issue are to publish original and review papers dealing with multimodal optimization (MMO). We invite works covering various optimization problem domains (single/multi-objective, continuous/numeric, discrete/combinatorial) as well as papers in the realm of machine learning (ML) and algorithm configuration, where configuration landscapes are oftentimes multi-objective and multimodal simultaneously. This Special Issue will mainly deal with evolutionary algorithms; however, non-evolutionary approaches are welcome as well.
Topics of interest include, but are not limited to, the following:
- Single- and multi-objective multimodal optimization;
- Connections of single-objective and multi-objective multimodal optimization;
- Continuous and combinatorial optimization;
- Connections of continuous and combinatorial optimization;
- Theoretical concepts for multimodality;
- Algorithm design;
- Automated algorithm selection and configuration;
- Function generators;
- Landscape analysis focusing on multimodality;
- Performance measurement.
Prof. Dr. Heike Trautmann
Dr. Lennart Schaepermeier
Prof. Dr. Oliver Schütze
Guest Editors
Manuscript Submission Information
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Keywords
- single- and multi-objective multimodal optimization
- continuous and combinatorial optimization
- multimodality
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