131 citations · 142 across the 9 of their papers we have counts for
9 papers
ATLAS: Scaffold-Free Algorithm Synthesis by LLMs via Embedding-Guided Quality-Diversity Search
Danial Yazdani, Mohammad Nabi Omidvar, Yuan Sun +2
Most LLM-based automated algorithm design methods optimize a designated component within a human-specified scaffold, fixing overall organization and component interactions. We pres…
PORTAL: Controllable Landscape Generator for Continuous Optimization-Part I: Framework
Danial Yazdani, Mai Peng, Delaram Yazdani +6
Benchmarking is central to optimization research, yet existing test suites for continuous optimization remain limited: classical collections are fixed and rigid, while previous gen…
Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes
Danial Yazdani, Juergen Branke, Mohammad Sadegh Khorshidi +4
Clustering in dynamic environments is of increasing importance, with broad applications ranging from real-time data analysis and online unsupervised learning to dynamic facility lo…
Semantic-Preserving Feature Partitioning for Multi-View Ensemble Learning
Mohammad Sadegh Khorshidi, Navid Yazdanjue, Hassan Gharoun +4
In machine learning, the exponential growth of data and the associated ``curse of dimensionality'' pose significant challenges, particularly with expansive yet sparse datasets. Add…
GNBG-Generated Test Suite for Box-Constrained Numerical Global Optimization
Amir H. Gandomi, Danial Yazdani, Mohammad Nabi Omidvar +1
This document introduces a set of 24 box-constrained numerical global optimization problem instances, systematically constructed using the Generalized Numerical Benchmark Generator…
EDOLAB: An Open-Source Platform for Education and Experimentation with Evolutionary Dynamic Optimization Algorithms
Mai Peng, Delaram Yazdani, Zeneng She +9
Many real-world optimization problems exhibit dynamic characteristics, posing significant challenges for traditional optimization techniques. Evolutionary Dynamic Optimization Algo…
Generating Large-scale Dynamic Optimization Problem Instances Using the Generalized Moving Peaks Benchmark
Mohammad Nabi Omidvar, Danial Yazdani, Juergen Branke +3
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)
Danial Yazdani, Michalis Mavrovouniotis, Changhe Li +6
The Generalized Moving Peaks Benchmark (GMPB) is a tool for generating continuous dynamic optimization problem instances with controllable dynamic and morphological characteristics…
A Review of the Family of Artificial Fish Swarm Algorithms: Recent Advances and Applications
Farhad Pourpanah, Ran Wang, Chee Peng Lim +2
The Artificial Fish Swarm Algorithm (AFSA) is inspired by the ecological behaviors of fish schooling in nature, viz., the preying, swarming and following behaviors. Owing to a numb…