Work

From understanding genetic drift to a smart-restart parameter-less compact genetic algorithm

Year: 2020

Type: conference-paper

Abstract: One of the key difficulties in using estimation-of-distribution algorithms is choosing the population sizes appropriately: Too small values lead to genetic drift, which can cause enormous difficulties. In the regime with no genetic drift, however, often the runtime is roughly proportional to the population size, which renders large population sizes inefficient.

Source: Genetic and Evolutionary Computation Conference (GECCO)

DOI: 10.1145/3377930.3390163

Authors: Benjamin Doerr, Weijie Zheng

Institutions: Institut Polytechnique de Paris, Southern University of Science and Technology

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green