Deb, 3d-radvis: visualization of Pareto front in many-objective optimization, in Congress on Evolutionary Computation (CEC), (IEEE Press, 2016), pp. Stanley, DNA visual and analytic data mining, in Visualization’97 (Cat. Kipouros, Interactive multi-objective particle swarm optimisation using decision space interaction, in Congress on Evolutionary Computation (CEC), (IEEE Press, 2013), pp. Mostaghim, Interactive multi-objective particle swarm optimization with heatmap-visualization-based user interface. Kipouros, A web-based system for visualisation-driven interactive multi-objective optimisation. Alba, A multi-objective evolutionary algorithm based on parallel coordinates, in Genetic and Evolutionary Computation Conference (GECCO), (ACM Press, 2016), pp. Characklis, Beyond optimality: multistakeholder robustness tradeoffs for regional water portfolio planning under deep uncertainty. Characklis, How should robustness be defined for water systems planning under change? J. Yen, Visualization and performance metric in many-objective optimization. Klamroth, Interactive nonconvex pareto navigator for multiobjective optimization. Matković, Task-based visual analytics for interactive multiobjective optimization. Reed, Borg: an auto-adaptive many-objective evolutionary computing framework. Keller, An open source framework for many-objective robust decision making. Reed, Rhodium: Python library for many-objective robust decision making and exploratory modeling. Characklis, Identifying actionable compromises: navigating multi-city robustness conflicts to discover cooperative safe operating spaces for regional water supply portfolios. Li, Visualisation of pareto front approximation: a short survey and empirical comparisons, in Congress on Evolutionary Computation (CEC), (IEEE Press, 2019), pp. Tušar, Visualization in multiobjective optimization, in Understanding Complexity in Multiobjective Optimization (Dagstuhl Seminar 15031), (Dagstuhl Zentrum für Informatik, 2015), pp. Tušar, A taxonomy of methods for visualizing pareto front approximations, in Genetic and Evolutionary Computation Conference (GECCO), (ACM Press, 2018), pp. Miettinen, A feature rich distance-based many-objective visualisable test problem generator, in Genetic and Evolutionary Computation Conference (GECCO), (ACM Press, 2019), pp. Kwakkel, Including robustness considerations in the search phase of many-objective robust decision making. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, (Wiley, Chichester, UK, 2001) Hall, Inferential performance assessment of stochastic optimisers and the attainment function, in Evolutionary Multi-criterion Optimization (EMO), (Springer, 2001), pp. Antunes, Implementation of a user-friendly software package–a guided tour of TRIMAP. Design Report for ME8104, Georgia Institute of Technology, (USA, 1995) Virasak, Designing a general aviation aircraft as an open engineering system. Maréchal, Interactive optimization with parallel coordinates: exploring multidimensional spaces for decision support. Ranjithan, MGA: a decision support system for complex, incompletely defined problems. Słowiński (eds), Multiobjective Optimization: Interactive and Evolutionary Approaches. Blasco, Interactive tool for decision making in multiobjective optimization with level diagrams. Deb, pymoo: multi-objective optimization in python. Piringer, Interactive visual analysis of multiobjective optimizations, in IEEE Symposium on Visual Analytics Science and Technology, (IEEE Press, 2010), pp. Stewart, Problem structuring and multiple criteria decision analysis, in Trends in Multiple Criteria Decision Analysis, ed. Ibrahim, Proposing a pareto-VIKOR ranking method for enhancing parallel coordinates visualization, in International Conference on Computer Science & Education (ICCSE 2019), (IEEE Press, 2019), pp. Apparently JIT compilation is very effective on such simple for-loops.K. The most suprising result to me is the last one. The timings (in the same order they are defined above): > testAntiDiag This was tested on 64-bit R2013a using TIMEIT function. Below is a comparison of all the methods mentioned so far, plus a few other variations I could think of.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |