48 citations · 134 across the 20 of their papers we have counts for
21 papers
When to Use Which? Benchmarking Optimisers for Configurable Systems under Varying Budgets
Chao Jiang, Yulong Ye, Tao Chen +1
Software configuration tuning is crucial for optimising system performance, and various optimisers have emerged over the last decade. Yet, the time required during the tuning proce…
On Scalability of Multi-Objective Evolutionary Algorithms on Combinatorial Optimisation Problems
Menghao Tang, Zimin Liang, Miqing Li
Scalability of evolutionary algorithms refers to assessing how their performance changes as problem size increases. In the area of multi-objective optimisation, research on the sca…
Do We Really Need to Approach the Entire Pareto Front in Many-Objective Bayesian Optimisation?
Chao Jiang, Jingyu Huang, Miqing Li
Many-objective optimisation, a subset of multi-objective optimisation, involves optimisation problems with more than three objectives. As the number of objectives increases, the nu…
Revealing Domain-Spatiality Patterns for Configuration Tuning: Domain Knowledge Meets Fitness Landscapes
Yulong Ye, Hongyuan Liang, Chao Jiang +2
Configuration tuning for better performance is crucial in quality assurance. Yet, there has long been a mystery on tuners' effectiveness, due to the black-box nature of configurabl…
Variable Search Stepsize for Randomized Local Search in Multi-Objective Combinatorial Optimization
Xuepeng Ren, Maocai Wang, Guangming Dai +4
Over the past two decades, research in evolutionary multi-objective optimization has predominantly focused on continuous domains, with comparatively limited attention given to mult…
Random is Faster than Systematic in Multi-Objective Local Search
Zimin Liang, Miqing Li
Local search is a fundamental method in operations research and combinatorial optimisation. It has been widely applied to a variety of challenging problems, including multi-objecti…
Uncertainty-Aware Offline Data-Driven Multi-Objective Optimization
Huanbo Lyu, Miqing Li, Shiqiao Zhou +7
In offline data-driven multi-objective optimization (MOO), optimization is performed using surrogate models trained only on an offline dataset. These surrogate models contain inher…
Not Just for Archiving: Provable Benefits of Reusing the Archive in Evolutionary Multi-objective Optimization
Shengjie Ren, Zimin Liang, Miqing Li +1
Evolutionary Algorithms (EAs) have become the most popular tool for solving widely-existed multi-objective optimization problems. In Multi-Objective EAs (MOEAs), there is increasin…
When to Truncate the Archive? On the Effect of the Truncation Frequency in Multi-Objective Optimisation
Zhiji Cui, Zimin Liang, Lie Meng Pang +2
Using an archive to store nondominated solutions found during the search of a multi-objective evolutionary algorithm (MOEA) is a useful practice. However, as nondominated solutions…
On the Problem Characteristics of Multi-objective Pseudo-Boolean Functions in Runtime Analysis
Zimin Liang, Miqing Li
Recently, there has been growing interest within the theoretical community in analytically studying multi-objective evolutionary algorithms. This runtime analysis-focused research…
A Weight Adaptation Trigger Mechanism in Decomposition-based Evolutionary Multi-Objective Optimisation
Xiaofeng Han, Xiaochen Chu, Tao Chao +2
Decomposition-based multi-objective evolutionary algorithms (MOEAs) are widely used for solving multi-objective optimisation problems. However, their effectiveness depends on the c…
A Theoretical Perspective on Why Stochastic Population Update Needs an Archive in Evolutionary Multi-objective Optimization
Shengjie Ren, Zimin Liang, Miqing Li +1
Evolutionary algorithms (EAs) have been widely applied to multi-objective optimization due to their population-based nature. Population update, a key component in multi-objective E…
Distilled Lifelong Self-Adaptation for Configurable Systems
Yulong Ye, Tao Chen, Miqing Li
Modern configurable systems provide tremendous opportunities for engineering future intelligent software systems. A key difficulty thereof is how to effectively self-adapt the conf…
Maintaining Diversity Provably Helps in Evolutionary Multimodal Optimization
Shengjie Ren, Zhijia Qiu, Chao Bian +2
In the real world, there exist a class of optimization problems that multiple (local) optimal solutions in the solution space correspond to a single point in the objective space. I…
An Archive Can Bring Provable Speed-ups in Multi-Objective Evolutionary Algorithms
Chao Bian, Shengjie Ren, Miqing Li +1
In the area of multi-objective evolutionary algorithms (MOEAs), there is a trend of using an archive to store non-dominated solutions generated during the search. This is because 1…
A First Running Time Analysis of the Strength Pareto Evolutionary Algorithm 2 (SPEA2)
Shengjie Ren, Chao Bian, Miqing Li +1
Evolutionary algorithms (EAs) have emerged as a predominant approach for addressing multi-objective optimization problems. However, the theoretical foundation of multi-objective EA…
Adapting Multi-objectivized Software Configuration Tuning
Tao Chen, Miqing Li
When tuning software configuration for better performance (e.g., latency or throughput), an important issue that many optimizers face is the presence of local optimum traps, compou…
Do Performance Aspirations Matter for Guiding Software Configuration Tuning?
Tao Chen, Miqing Li
Configurable software systems can be tuned for better performance. Leveraging on some Pareto optimizers, recent work has shifted from tuning for a single, time-related performance…
The Weights can be Harmful: Pareto Search versus Weighted Search in Multi-Objective Search-Based Software Engineering
Tao Chen, Miqing Li
In presence of multiple objectives to be optimized in Search-Based Software Engineering (SBSE), Pareto search has been commonly adopted. It searches for a good approximation of the…
MMO: Meta Multi-Objectivization for Software Configuration Tuning
Pengzhou Chen, Tao Chen, Miqing Li
Software configuration tuning is essential for optimizing a given performance objective (e.g., minimizing latency). Yet, due to the software's intrinsically complex configuration l…
Multi-Objectivizing Software Configuration Tuning (for a single performance concern)
Tao Chen, Miqing Li
Automatically tuning software configuration for optimizing a single performance attribute (e.g., minimizing latency) is not trivial, due to the nature of the configuration systems…