Maximizing Drift is Not Optimal for Solving OneMax

Simple Hyper-heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes*

(2019) Andrei Lissovoi et al.   EVOLUTIONARY COMPUTATION

Optimal parameter choices via precise black-box analysis

(2019) Benjamin Doerr et al.   THEORETICAL COMPUTER SCIENCE

Probabilistic Analysis of the (1+1)-Evolutionary Algorithm

(2018) Hsien-Kuei Hwang et al.   EVOLUTIONARY COMPUTATION

The (1+λ) Evolutionary Algorithm with Self-Adjusting Mutation Rate

(2018) Benjamin Doerr et al.   ALGORITHMICA

Introducing Elitist Black-Box Models: When Does Elitist Behavior Weaken the Performance of Evolutionary Algorithms?

(2017) Carola Doerr et al.   EVOLUTIONARY COMPUTATION

A Systematic Literature Review of Adaptive Parameter Control Methods for Evolutionary Algorithms

(2016) Aldeida Aleti et al.   ACM COMPUTING SURVEYS

On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation

(2016) Dogan Corus et al.   ALGORITHMICA

The Impact of Random Initialization on the Runtime of Randomized Search Heuristics

(2015) Benjamin Doerr et al.   ALGORITHMICA

Parameter Control in Evolutionary Algorithms: Trends and Challenges

(2015) Giorgos Karafotias et al.   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

Exact computation of the expectation surfaces for uniform crossover along with bit-flip mutation

(2014) Francisco Chicano et al.   THEORETICAL COMPUTER SCIENCE

Tight Bounds on the Optimization Time of a Randomized Search Heuristic on Linear Functions

(2013) CARSTEN WITT   COMBINATORICS PROBABILITY & COMPUTING

Multiplicative Drift Analysis

(2012) Benjamin Doerr et al.   ALGORITHMICA

A New Method for Lower Bounds on the Running Time of Evolutionary Algorithms

(2012) Dirk Sudholt   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION