Search Results for author:
Found 6 papers, 5 papers with code
Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes
Clustering in dynamic environments is of increasing importance, with broad applications ranging from real-time data analysis and online unsupervised learning to dynamic facility location problems.
GNBG: A Generalized and Configurable Benchmark Generator for Continuous Numerical Optimization
To effectively assess, validate, and compare optimization algorithms, it is crucial to use a benchmark test suite that encompasses a diverse range of problem instances with various characteristics.
GNBG-Generated Test Suite for Box-Constrained Numerical Global Optimization
This document introduces a set of 24 box-constrained numerical global optimization problem instances, systematically constructed using the Generalized Numerical Benchmark Generator (GNBG).
Variable Functioning and Its Application to Large Scale Steel Frame Design Optimization
By using problem structure analysis technique and engineering expert knowledge, the $Fx$ method is used to enhance the steel frame design optimization process as a complex real-world problem.
Generating Large-scale Dynamic Optimization Problem Instances Using the Generalized Moving Peaks Benchmark
This document describes the generalized moving peaks benchmark (GMPB) and how it can be used to generate problem instances for continuous large-scale dynamic optimization problems.
Competition on Dynamic Optimization Problems Generated by Generalized Moving Peaks Benchmark (GMPB)
This document introduces the Generalized Moving Peaks Benchmark (GMPB), a tool for generating continuous dynamic optimization problem instances that is used for the CEC 2024 Competition on Dynamic Optimization.
