dPSO‐Vis: Topology‐based Visualization of Discrete Particle Swarm Optimization

Volke, Sebastian; Middendorf, Martin; Hlawitschka, Mario; Kasten, Jens; Zeckzer, Dirk; Scheuermann, Gerik

doi:10.1111/cgf.12122

Cited by 10 publications

(3 citation statements)

References 22 publications

(35 reference statements)

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“…For example, Oesterling et al [24] propose 1D topological landscape profiles for multi-dimensional point clouds, where each superarc is represented by a hill-like icon parameterized by size and persistence of that superarc. Similar 1D topological landscape profiles have also been introduced for barrier trees [40,41] of optimization landscapes and level set trees [17] of density estimates. Under specific parameter settings and applied to scalar fields, these yield equivalent results to our proposed domain linearization.…”

Section: Visualization and Tracking Of (Augmented) Merge Treesmentioning

confidence: 99%

Temporal Merge Tree Maps:A Topology-Based Static Visualization for Temporal Scalar Data

Köpp

Weinkauf

2022

IEEE Trans. Visual. Comput. Graphics

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strong storm over Scandinavia strong storm over the British Isles and Norway cyclone Lothar cyclone Martin -35 0 35 sea level pressure anomaly [hPa] linearized space linearized space Figure 1. A temporal merge tree map (top) is a static visualization of a time-dependent scalar field (bottom). Our method uses augmented merge trees to map the data samples of each time step to a vertical slice. An optimization scheme is employed to achieve a temporally coherent mapping. The shown Storms data set represents storm activity over Europe in December 1999 and contains 744 time steps, arranged from left to right. Cyclones can easily be identified as dark blue lines and compared with each other wrt. their strength, lifetime, and footprint, while still being shown in the context of the entire data. Temporal merge tree maps can serve as data analysis tools in their own right, or be used to augment animations and other views. With some parallel processing, the above image can be computed in less than 15 seconds.

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Section: Visualization and Tracking Of (Augmented) Merge Treesmentioning

confidence: 99%

Temporal Merge Tree Maps:A Topology-Based Static Visualization for Temporal Scalar Data

Köpp

Weinkauf

2022

IEEE Trans. Visual. Comput. Graphics

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“…This is the analog of the volume plot for merge trees of functions that are not piecewise constant. Volke et al [VMH*13] construct a landscape profile for a barrier tree. They then overlay regions in the landscape with histograms showing the performance of different swarm optimization algorithms that operate in the space.…”

Section: State Of the Art – Scalar Fieldsmentioning

confidence: 99%

A Survey of Topology‐based Methods in Visualization

Heine

Leitte

Hlawitschka³

et al. 2016

Computer Graphics Forum

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130

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This paper presents the state of the art in the area of topology-based visualization. It describes the process and results of an extensive annotation for generating a definition and terminology for the field. The terminology enabled a typology for topological models which is used to organize research results and the state of the art. Our report discusses relations among topological models and for each model describes research results for the computation, simplification, visualization, and application. The paper identifies themes common to subfields, current frontiers, and unexplored territory in this research area.

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“…This work has been used in the analysis and visualization of combinatorial optimization [1,14,27,28]. However, all of these methods require the set of all solutions below a certain cost threshold to be available.…”

Section: Related Workmentioning

confidence: 99%

A Visual Method for Analysis and Comparison of Search Landscapes

Volke

Zeckzer

Scheuermann

et al. 2015

Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation

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Combinatorial optimization problems and corresponding (meta-)heuristics have received much attention in the literature. Especially, the structural or topological analysis of search landscapes is important for evaluating the applicability and the performance of search operators for a given problem. However, this analysis is often tedious and usually the focus is on one specific problem and only a few operators. We present a visual analysis method that can be applied to a wide variety of problems and search operators. The method is based on steepest descent walks and shortest distances in the search landscape. The visualization shows the search landscape as seen by the search algorithm. It supports the topological analysis as well as the comparison of search landscapes. We showcase the method by applying it to two different search operators on the TSP, the QAP, and the SMTTP. Our results show how differences between search operators manifest in the search landscapes and how conclusions about the suitability of the search operator for different optimizations can be drawn.

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dPSO‐Vis: Topology‐based Visualization of Discrete Particle Swarm Optimization

Cited by 10 publications

References 22 publications

Temporal Merge Tree Maps:A Topology-Based Static Visualization for Temporal Scalar Data

Temporal Merge Tree Maps:A Topology-Based Static Visualization for Temporal Scalar Data

A Survey of Topology‐based Methods in Visualization

A Visual Method for Analysis and Comparison of Search Landscapes

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