21 citations · 100 across the 35 of their papers we have counts for
6 papers · 1 filter
Benchmarking Discrete Optimization Heuristics with IOHprofiler
Carola Doerr, Furong Ye, Naama Horesh +3
Automated benchmarking environments aim to support researchers in understanding how different algorithms perform on different types of optimization problems. Such comparisons provi…
Modeling User Selection in Quality Diversity
Alexander Hagg, Alexander Asteroth, Thomas Bäck
The initial phase in real world engineering optimization and design is a process of discovery in which not all requirements can be made in advance, or are hard to formalize. Qualit…
SACOBRA with Online Whitening for Solving Optimization Problems with High Conditioning
Samineh Bagheri, Wolfgang Konen, Thomas Bäck
Real-world optimization problems often have expensive objective functions in terms of cost and time. It is desirable to find near-optimal solutions with very few function evaluatio…
Online Selection of CMA-ES Variants
Diederick Vermetten, Sander van Rijn, Thomas Bäck +1
In the field of evolutionary computation, one of the most challenging topics is algorithm selection. Knowing which heuristics to use for which optimization problem is key to obtain…
Efficient Computation of Expected Hypervolume Improvement Using Box Decomposition Algorithms
Kaifeng Yang, Michael Emmerich, André Deutz +1
In the field of multi-objective optimization algorithms, multi-objective Bayesian Global Optimization (MOBGO) is an important branch, in addition to evolutionary multi-objective op…
Interpolating Local and Global Search by Controlling the Variance of Standard Bit Mutation
Furong Ye, Carola Doerr, Thomas Bäck
A key property underlying the success of evolutionary algorithms (EAs) is their global search behavior, which allows the algorithms to `jump' from a current state to other parts of…