1 code implementation • 6 Apr 2024 • Tao Chen, Miqing Li
Experiments on several real-world systems, objectives, and budgets show that, for 71% of the cases, AdMMO is considerably superior to MMO and a wide range of state-of-the-art optimizers while achieving generally better efficiency with the best speedup between 2. 2x and 20x.
no code implementations • 5 Jun 2023 • Chao Bian, Yawen Zhou, Miqing Li, Chao Qian
This work is an attempt to challenge a common practice in the design of existing MOEAs.
no code implementations • 26 May 2023 • Zimin Liang, Miqing Li, Per Kristian Lehre
Elitism, which constructs the new population by preserving best solutions out of the old population and newly-generated solutions, has been a default way for population update since its introduction into multi-objective evolutionary algorithms (MOEAs) in the late 1990s.
no code implementations • 16 Mar 2023 • Miqing Li, Manuel López-Ibáñez, Xin Yao
Such an archive can be solely used to store high-quality solutions presented to the decision maker, but in many cases may participate in the search process (e. g., as the population in evolutionary computation).
1 code implementation • 9 Jan 2023 • Tao Chen, Miqing Li
Before we design better optimizers, a crucial engineering decision to make therein is how to handle the performance requirements with clear aspirations in the tuning process.
1 code implementation • 13 Oct 2022 • Ke Xue, Jiacheng Xu, Lei Yuan, Miqing Li, Chao Qian, Zongzhang Zhang, Yang Yu
MA-DAC formulates the dynamic configuration of a complex algorithm with multiple types of hyperparameters as a contextual multi-agent Markov decision process and solves it by a cooperative multi-agent RL (MARL) algorithm.
no code implementations • 31 May 2022 • Yani Xue, Miqing Li, Xiaohui Liu
In such problems, classic Pareto-based algorithms fail to provide sufficient selection pressure towards the Pareto front, whilst recently developed algorithms, such as decomposition-based ones, may struggle to maintain a set of well-distributed solutions on certain problems (e. g., those with irregular Pareto fronts).
1 code implementation • 8 Feb 2022 • Tao Chen, Miqing Li
However, when clear preferences of the stakeholders (e. g., a set of weights which reflect relative importance between objectives) are available prior to the search, weighted search is believed to be the first choice since it simplifies the search via converting the original multi-objective problem into a single-objective one and enable the search to focus on what only the stakeholders are interested in.
1 code implementation • 14 Dec 2021 • Pengzhou Chen, Tao Chen, Miqing Li
We also demonstrate that the MMO model with the new normalization can consolidate recent model-based tuning tools on 68% of the cases with up to 1. 22x speedup in general.
no code implementations • 31 May 2021 • 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 (e. g., complex landscape and expensive measurement).
1 code implementation • 20 Feb 2020 • Miqing Li, Tao Chen, Xin Yao
We then conduct an in-depth analysis of quality evaluation indicators/methods and general situations in SBSE, which, together with the identified issues, enables us to codify a methodological guidance for selecting and using evaluation methods in different SBSE scenarios.
1 code implementation • 22 Jan 2020 • Tao Chen, Miqing Li, Ke Li, Kalyanmoy Deb
In this paper, we provide the first systematic and comprehensive survey exclusively on SBSE for SASs, covering papers in 27 venues from 7 repositories, which eventually leads to several key statistics from the most notable 74 primary studies in this particular field of research.
no code implementations • 7 Jun 2018 • Liangli Zhen, Miqing Li, Ran Cheng, Dezhong Peng, Xin Yao
The redundancy of some objectives can lead to the multiobjective problem having a degenerate Pareto front, i. e., the dimension of the Pareto front of the $m$-objective problem be less than (m-1).
no code implementations • 8 Sep 2017 • Miqing Li, Xin Yao
A set of weights distributed uniformly in a simplex often lead to a set of well-distributed solutions on a Pareto front with a simplex-like shape, but may fail on other Pareto front shapes.
no code implementations • 30 Apr 2017 • Miqing Li, Liangli Zhen, Xin Yao
In this paper, we make some observations of the parallel coordinates plot, in terms of comparing the quality of solution sets, understanding the shape and distribution of a solution set, and reflecting the relation between objectives.
no code implementations • 1 Feb 2017 • Miqing Li, Xin Yao
In this paper, we propose a quality measure, called dominance move (DoM), to compare solution sets generated by multiobjective optimizers.
1 code implementation • IEEE Transactions on Evolutionary Computation 2013 • Shengxiang Yang, Member, IEEE, Miqing Li, Xiaohui Liu, and Jinhua Zheng
Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO).