1 code implementation • 24 Feb 2024 • Danial Yazdani, Juergen Branke, Mohammad Sadegh Khorshidi, Mohammad Nabi Omidvar, XiaoDong Li, Amir H. Gandomi, Xin Yao
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.
1 code implementation • 12 Dec 2023 • Danial Yazdani, Mohammad Nabi Omidvar, Delaram Yazdani, Kalyanmoy Deb, Amir H. Gandomi
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.
1 code implementation • 12 Dec 2023 • Amir H. Gandomi, Danial Yazdani, Mohammad Nabi Omidvar, Kalyanmoy Deb
This document introduces a set of 24 box-constrained numerical global optimization problem instances, systematically constructed using the Generalized Numerical Benchmark Generator (GNBG).
no code implementations • 15 May 2022 • Amir H Gandomi, Kalyanmoy Deb, Ronald C Averill, Shahryar Rahnamayan, Mohammad Nabi Omidvar
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.
1 code implementation • 23 Jul 2021 • Mohammad Nabi Omidvar, Danial Yazdani, Juergen Branke, XiaoDong Li, Shengxiang Yang, Xin Yao
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.
1 code implementation • 11 Jun 2021 • Danial Yazdani, Michalis Mavrovouniotis, Changhe Li, Wenjian Luo, Mohammad Nabi Omidvar, Amir H. Gandomi, Trung Thanh Nguyen, Juergen Branke, XiaoDong Li, Shengxiang Yang, Xin Yao
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.