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20122026
most citedEvolutionary Multitasking for Single-objective Continuous Optimization: Benchmark Problems, Performance Metric, and Baseline Results

137 citations · 137 across the 6 of their papers we have counts for

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cs.NE2026

Evolutionary Computation for Trustworthy AI: From Attacks and Defenses to Self-Evolving Era

Junhao Dong, Chenkai Wang, Xuanhui Lin +8

As Artificial Intelligence (AI) has evolved from task-specific models to foundation models and agents, the scope of trustworthy AI has expanded from model-level robustness to the r…

cs.NE2026

Online Regime-aware Calibration for Black-box Social Simulators via Posterior-assisted Evolutionary Dynamic Optimization

Peng Yang, Zhenhua Yang, Boquan Jiang +3

Evolutionary dynamic optimization (EDO) commonly assumes that environmental changes can be detected from fitness variations and handled through random re-initialization, historical…

cs.NE2025

Knowledge-Guided Memetic Algorithm for Capacitated Arc Routing Problems with Time-Dependent Service Costs

Qingya Li, Shengcai Liu, Wenjie Chen +3

The capacitated arc routing problem with time-dependent service costs (CARPTDSC) is a challenging combinatorial optimization problem that arises from winter gritting applications.…

cs.NE2024

MEGO: Learning Mixture-of-Experts for General-Purpose Binary Optimization

Shengcai Liu, Zhiyuan Wang, Yew-Soon Ong +2

Discrete optimization is ubiquitous in science and engineering. The vast array of existing discrete optimization problems, coupled with the continuous emergence of new ones, necess…

cs.NE2017★ 137 cited

Evolutionary Multitasking for Single-objective Continuous Optimization: Benchmark Problems, Performance Metric, and Baseline Results

Bingshui Da, Yew-Soon Ong, Liang Feng +6

In this report, we suggest nine test problems for multi-task single-objective optimization (MTSOO), each of which consists of two single-objective optimization tasks that need to b…

cs.NE2012

A Large Population Size Can Be Unhelpful in Evolutionary Algorithms

Tianshi Chen, Ke Tang, Guoliang Chen +1

The utilization of populations is one of the most important features of evolutionary algorithms (EAs). There have been many studies analyzing the impact of different population siz…