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

SATzilla: Portfolio-based Algorithm Selection for SAT

(2018) L. Xu et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

A Large-Scale Experimental Evaluation of High-Performing Multi- and Many-Objective Evolutionary Algorithms

(2017) Leonardo C. T. Bezerra et al.   EVOLUTIONARY COMPUTATION

Principled Design and Runtime Analysis of Abstract Convex Evolutionary Search

(2017) Alberto Moraglio et al.   EVOLUTIONARY COMPUTATION

Standard Steady State Genetic Algorithms Can Hillclimb Faster than Mutation-only Evolutionary Algorithms

(2017) Dogan Corus et al.   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

Level-Based Analysis of Genetic Algorithms and Other Search Processes

(2017) Dogan Corus et al.   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

Improved time complexity analysis of the Simple Genetic Algorithm

(2015) Pietro S. Oliveto et al.   THEORETICAL COMPUTER SCIENCE

A unified hyper-heuristic framework for solving bin packing problems

(2014) Eunice López-Camacho et al.   EXPERT SYSTEMS WITH APPLICATIONS

Hyper-heuristics: a survey of the state of the art

(2013) Edmund K Burke et al.   JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY

On the runtime analysis of the Simple Genetic Algorithm

(2013) Pietro S. Oliveto et al.   THEORETICAL COMPUTER SCIENCE

Black-Box Search by Unbiased Variation

(2012) Per Kristian Lehre et al.   ALGORITHMICA