Output details
11 - Computer Science and Informatics
University of Sheffield
A New Method for Lower Bounds on the Running Time of Evolutionary Algorithms
<12>The paper introduces an easy-to-use method for achieving a notoriously difficult task: proving lower runtime bounds for evolutionary algorithms. The lower bounds results apply to all mutation-based evolutionary algorithms (as opposed to a single one), allowing optimal designs of evolutionary algorithms to be designed for the first time. The method has become a standard technique as featured in tutorials at international conference series (ACM-GECCO, IEEE-CEC, ThRaSH) and textbooks (including Springer ISBN-978-3-642-17338-7). With preliminary versions it has 23 GoogleScholar cites. IEEE TEVC has an A* ERA ranking, with an IF of 4.81 and is 1/100 in Computer Science, Theory and Methods.