Landscape-aware performance prediction for evolutionary multiobjective optimization

A Liefooghe, F Daolio, S Verel, B Derbel… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
We expose and contrast the impact of landscape characteristics on the performance of
search heuristics for black-box multiobjective combinatorial optimization problems. A sound …

Automated algorithm selection on continuous black-box problems by combining exploratory landscape analysis and machine learning

P Kerschke, H Trautmann - Evolutionary computation, 2019 - direct.mit.edu
In this article, we build upon previous work on designing informative and efficient
Exploratory Landscape Analysis features for characterizing problems' landscapes and show …

Comprehensive feature-based landscape analysis of continuous and constrained optimization problems using the R-package flacco

P Kerschke, H Trautmann - … in Statistical Computing: From Music Data …, 2019 - Springer
Choosing the best-performing optimizer (s) out of a portfolio of optimization algorithms is
usually a difficult and complex task. It gets even worse, if the underlying functions are …

[HTML][HTML] What if we increase the number of objectives? Theoretical and empirical implications for many-objective combinatorial optimization

R Allmendinger, A Jaszkiewicz, A Liefooghe… - Computers & Operations …, 2022 - Elsevier
The difficulty of solving a multi-objective optimization problem is impacted by the number of
objectives to be optimized. The presence of many objectives typically introduces a number …

MOEAs are stuck in a different area at a time

M Li, X Han, X Chu - Proceedings of the Genetic and Evolutionary …, 2023 - dl.acm.org
In this paper, we show that when dealing with multi-objective combinatorial optimisation
problems, the search, in different executions of a multi-objective evolutionary algorithm …

[HTML][HTML] Characterization of constrained continuous multiobjective optimization problems: A feature space perspective

A Vodopija, T Tušar, B Filipič - Information Sciences, 2022 - Elsevier
Despite the increasing interest in constrained multiobjective optimization in recent years,
constrained multiobjective optimization problems (CMOPs) are still insufficiently understood …

On Pareto local optimal solutions networks

A Liefooghe, B Derbel, S Verel, M López-Ibáñez… - Parallel Problem Solving …, 2018 - Springer
Pareto local optimal solutions (PLOS) are believed to highly influence the dynamics and the
performance of multi-objective optimization algorithms, especially those based on local …

Pareto local optimal solutions networks with compression, enhanced visualization and expressiveness

A Liefooghe, G Ochoa, S Verel, B Derbel - Proceedings of the Genetic …, 2023 - dl.acm.org
The structure of local optima in multi-objective combinatorial optimization and their impact
on algorithm performance are not yet properly understood. In this paper, we are interested in …

Search dynamics on multimodal multiobjective problems

P Kerschke, H Wang, M Preuss, C Grimme… - Evolutionary …, 2019 - direct.mit.edu
We continue recent work on the definition of multimodality in multiobjective optimization
(MO) and the introduction of a test bed for multimodal MO problems. This goes beyond well …

A metaheuristic-based efficient strategy for multi-unit production planning with unique process constraints

R Kommadath, D Maharana, P Kotecha - Applied Soft Computing, 2023 - Elsevier
Production planning provides optimal strategic planning to attain economic benefits in the
petrochemical industries and helps to maintain competitiveness in the global market. This …