Theory of parameter control for discrete black-box optimization: Provable performance gains through dynamic parameter choices
Parameter control is aimed at realizing performance gains through a dynamic choice of the
parameters which determine the behavior of the underlying optimization algorithm. In the …
parameters which determine the behavior of the underlying optimization algorithm. In the …
A survey on recent progress in the theory of evolutionary algorithms for discrete optimization
The theory of evolutionary computation for discrete search spaces has made significant
progress since the early 2010s. This survey summarizes some of the most important recent …
progress since the early 2010s. This survey summarizes some of the most important recent …
Probabilistic tools for the analysis of randomized optimization heuristics
B Doerr - … of evolutionary computation: Recent developments in …, 2020 - Springer
This chapter collects several probabilistic tools that have proven to be useful in the analysis
of randomized search heuristics. This includes classic material such as the Markov …
of randomized search heuristics. This includes classic material such as the Markov …
A proof that using crossover can guarantee exponential speed-ups in evolutionary multi-objective optimisation
Evolutionary algorithms are popular algorithms for multiobjective optimisation (also called
Pareto optimisation) as they use a population to store trade-offs between different objectives …
Pareto optimisation) as they use a population to store trade-offs between different objectives …
Benchmarking discrete optimization heuristics with IOHprofiler
Automated benchmarking environments aim to support researchers in understanding how
different algorithms perform on different types of optimization problems. Such comparisons …
different algorithms perform on different types of optimization problems. Such comparisons …
A modified sine cosine algorithm for solving optimization problems
M Wang, G Lu - Ieee Access, 2021 - ieeexplore.ieee.org
The sine cosine algorithm (SCA) is a newly emerging optimization algorithm. It is easy for
sine cosine algorithm (SCA) to sink into premature of the algorithm and obtain a slower …
sine cosine algorithm (SCA) to sink into premature of the algorithm and obtain a slower …
Self-adjusting evolutionary algorithms for multimodal optimization
Recent theoretical research has shown that self-adjusting and self-adaptive mechanisms
can provably outperform static settings in evolutionary algorithms for binary search spaces …
can provably outperform static settings in evolutionary algorithms for binary search spaces …
Applying genetic algorithm and ant colony optimization algorithm into marine investigation path planning model
Y Liang, L Wang - Soft Computing, 2020 - Springer
Marine resources are vital to the development of a country. Marine investigation can obtain
more marine resources and acquire more marine environmental information. A common …
more marine resources and acquire more marine environmental information. A common …
[HTML][HTML] Segmented trajectory planning strategy for active collision avoidance system
H Zhang, C Liu, W Zhao - Green Energy and Intelligent Transportation, 2022 - Elsevier
This paper presents a segmented trajectory planning strategy for active collision avoidance
system. Considering the longitudinal and lateral movement of the obstacle vehicle, as well …
system. Considering the longitudinal and lateral movement of the obstacle vehicle, as well …
Fast mutation in crossover-based algorithms
The heavy-tailed mutation operator proposed in Doerr et al.(GECCO 2017), called fast
mutation to agree with the previously used language, so far was successfully used only in …
mutation to agree with the previously used language, so far was successfully used only in …