Maria Laura Santoni,Elena Raponi,Aneta Neumann et al.
Maria Laura Santoni et al.
In real-world applications, users often favor structurally diverse design choices over one high-quality solution. It is therefore important to consider more solutions that decision makers can compare and further explore based on additional ...
Deep-ELA: Deep Exploratory Landscape Analysis with Self-Supervised Pretrained Transformers for Single-Objective and Multiobjective Continuous Optimization Problems [0.03%]
基于自监督预训练变换器的深度探索式景观分析方法及其在单/多目标连续优化问题中的应用
Moritz Vinzent Seiler,Pascal Kerschke,Heike Trautmann
Moritz Vinzent Seiler
In many recent works, the potential of Exploratory Landscape Analysis (ELA) features to numerically characterize single-objective continuous optimization problems has been demonstrated. These numerical features provide the input for all kin...
On stochastic operators, fitness landscapes, and optimization heuristics performances [0.03%]
关于随机算子、适应度景观与启发式优化性能的研究
Brahim Aboutaib,Sébastien Verel,Cyril Fonlupt et al.
Brahim Aboutaib et al.
Stochastic operators are the backbone of many stochastic optimization algorithms. Besides the existing theoretical analysis that analyzes the asymptotic runtime of such algorithms, characterizing their performances using fitness landscapes ...
Cross-Representation Genetic Programming: A Case Study on Tree-based and Linear Representations [0.03%]
基于树和线性表示的交叉遗传编程：案例研究
Zhixing Huang,Yi Mei,Fangfang Zhang et al.
Zhixing Huang et al.
Existing genetic programming (GP) methods are typically designed based on a certain representation, such as tree-based or linear representations. These representations show various pros and cons in different domains. However, due to the com...
Genetic Programming with Tabu List for Dynamic Flexible Job Shop Scheduling [0.03%]
基于禁忌搜索的遗传算法在动态柔性作业车间调度中的应用研究
Fangfang Zhang,Mazhar Ansari Ardeh,Yi Mei et al.
Fangfang Zhang et al.
Dynamic flexible job shop scheduling (DFJSS) is an important combinatorial optimisation problem, requiring simultaneous decision-making for machine assignment and operation sequencing in dynamic environments. Genetic programming (GP), as a ...
BlindSMOTE: Synthetic minority oversampling based only on evolutionary computation [0.03%]
基于进化计算的合成少数过采样算法 BlindSMOTE
Nicolás E Garcí-Pedrajas,José M Cuevas-Muñoz,Aida de Haro-García
Nicolás E Garcí-Pedrajas
One of the most common problems in data mining applications is the uneven distribution of classes, which appears in many real-world scenarios. The class of interest is often highly underrepresented in the given dataset, which harms the perf...
Jeroen G Rook,Carolin Benjamins,Jakob Bossek et al.
Jeroen G Rook et al.
Automated algorithm configuration aims at finding well-performing parameter configurations for a given problem, and it has proven to be effective within many AI domains, including evolutionary computation. Initially, the focus was on excell...
Solving Many-objective Optimization Problems based on PF Shape Classification and Vector Angle Selection [0.03%]
基于PF形状分类和向量角选择的多目标优化问题求解方法研究
Y T Wu,F Z Ge,D B Chen et al.
Y T Wu et al.
Most many-objective optimization algorithms (MaOEAs) adopt a pre-assumed Pareto front (PF) shape, instead of the true PF shape, to balance convergence and diversity in high-dimensional objective space, resulting in insufficient selection pr...
Beyond Landscape Analysis: DynamoRep Features For Capturing Algorithm-Problem Interaction In Single-Objective Continuous Optimization [0.03%]
超越景观分析：DynamoRep特征用于捕获单目标连续优化中的算法问题相互作用
Gjorgjina Cenikj,Gašper Petelin,Carola Doerr et al.
Gjorgjina Cenikj et al.
The representation of optimization problems and algorithms in terms of numerical features is a well-established tool for comparing optimization problem instances, for analyzing the behavior of optimization algorithms, and the quality of exi...
On the use of the Doubly Stochastic Matrix models for the Quadratic Assignment Problem [0.03%]
双随机矩阵模型在赋值问题中的应用探讨
Valentino Santucci,Josu Ceberio
Valentino Santucci
Permutation problems have captured the attention of the combinatorial optimization community for decades due to the challenge they pose. Although their solutions are naturally encoded as permutations, in each problem, the information to be ...