An algorithm for drawing general undirected graphs
Information Processing Letters
Graph drawing by force-directed placement
Software—Practice & Experience
Human-guided simple search: combining information visualization and heuristic search
Proceedings of the 1999 workshop on new paradigms in information visualization and manipulation in conjunction with the eighth ACM internation conference on Information and knowledge management
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
N-to-2-Space Mapping for Visualization of Search Algorithm Performance
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Visualization, Optimization, and Business Strategy: A Case Study
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Visualization of Pareto-Sets in Evolutionary Multi-Objective Optimization
HIS '07 Proceedings of the 7th International Conference on Hybrid Intelligent Systems
IEEE Transactions on Visualization and Computer Graphics
Introduction to Multiobjective Optimization: Interactive Approaches
Multiobjective Optimization
On Effectively Finding Maximal Quasi-cliques in Graphs
Learning and Intelligent Optimization
Reactive Search and Intelligent Optimization
Reactive Search and Intelligent Optimization
Multicriteria decision making (MCDM): a framework for research and applications
IEEE Computational Intelligence Magazine
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This paper proposes a flexible software architecture for interactive multi-objective optimization, with a user interface for visualizing the results and facilitating the solution analysis and decision making process. The architecture is modular, it allows for problem-specific extensions, and it is applicable as a post-processing tool for all optimization schemes with a number of different potential solutions. When the architecture is tightly coupled to a specific problem-solving or optimization method, effective interactive schemes where the final decision maker is in the loop can be developed. An application to Reactive Search Optimization is presented. Visualization and optimization are connected through user interaction: the user is in the loop and the system rapidly reacts to user inputs, like specifying a focus of analysis, or preferences for exploring and intensifying the search in interesting areas. The novelty of the visualization approach consists of using recent online graph drawing techniques, with sampling and mental map preserving schemes, in the framework of stochastic local search optimization. Anecdotal results to demonstrate the effectiveness of the approach are shown for some relevant optimization tasks.