TOC GECCO 2020 Competitions, Workshops, Tutorials, HOP, LBAs (no abstract)

GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

Full Citation in the ACM Digital Library

SESSION: Competition entry: Competition evolutionary computation in the energy domain: Smart grid applications

Applying some EDAs and hybrid variants to the ERM problem under uncertainty

  • Yoan Martínez-López
  • Ansel Y. Rodríguez-González
  • Julio Madera Quintana
  • Miguel Bethencourt Mayedo
  • Alexis Moya
  • Oscar Martínez Santiago

SESSION: Competition entry: Competition on the optimal camera placement problem (OCP) and the unicost set covering problem (USCP)

Weighting-based parallel local search for optimal camera placement and unicost set covering

  • Weibo Lin
  • Fuda Ma
  • Zhouxing Su
  • Qingyun Zhang
  • Chumin Li
  • Zhipeng Lü

SESSION: Competition entry: Competition open optimization competition 2020

Deep statistics: more robust performance statistics for single-objective optimization benchmarking

  • Tome Eftimov
  • Gašper Petelin
  • Rok Hribar
  • Gorjan Popovski
  • Urban Škvorc
  • Peter Korošec

PerformViz: a machine learning approach to visualize and understand the performance of single-objective optimization algorithms

  • Tome Eftimov
  • Rok Hribar
  • Urban Škvorc
  • Gorjan Popovski
  • Gašper Petelin
  • Peter Korošec

SESSION: Competition entry: Competition on single objective bound constrained numerical optimization

SOMA-CL for competition on single objective bound constrained numerical optimization benchmark: a competition entry on single objective bound constrained numerical optimization at the genetic and evolutionary computation conference (GECCO) 2020

  • Tomas Kadavy
  • Michal Pluhacek
  • Adam Viktorin
  • Roman Senkerik

SESSION: Competition entry: Competition on single objective constrained numerical optimization

A modified covariance matrix adaptation evolution strategy for real-world constrained optimization problems

  • Abhishek Kumar
  • Swagatam Das
  • Ivan Zelinka

A self-adaptive spherical search algorithm for real-world constrained optimization problems

  • Abhishek Kumar
  • Swagatam Das
  • Ivan Zelinka

SESSION: Hot off the press

Sharp bounds for genetic drift in estimation of distribution algorithms (Hot-off-the-press track at GECCO 2020)

  • Benjamin Doerr
  • Weijie Zheng

The univariate marginal distribution algorithm copes well with deception and epistasis

  • Benjamin Doerr
  • Martin S. Krejca

Is the statistical significance between stochastic optimization algorithms' performances also significant in practice?

  • Tome Eftimov
  • Peter Korošec

Large scale biomedical data analysis with tree-based automated machine learning

  • Trang T. Le
  • Weixuan Fu
  • Jason H. Moore

Empirical linkage learning

  • Michal W. Przewozniczek
  • Marcin M. Komarnicki

SGP-DT: towards effective symbolic regression with a semantic GP approach based on dynamic targets

  • Stefano Ruberto
  • Valerio Terragni
  • Jason H. Moore

Using exploratory landscape analysis to visualize single-objective problems

  • Urban Škvorc
  • Tome Eftimov
  • Peter Korošec

SESSION: Late-breaking abstract

Combined kriging surrogate model for efficient global optimization using the optimal weighting method

  • Tanguy Appriou
  • Koji Shimoyama

A daily stock index predictor using feature selection based on a genetic wrapper

  • Dong-Hee Cho
  • Seung-Hyun Moon
  • Yong-Hyuk Kim

A genetic algorithm to optimize SMOTE and GAN ratios in class imbalanced datasets

  • Hwi-Yeon Cho
  • Yong-Hyuk Kim

Data driven building of realistic neuron model using IBEA and CMA evolution strategies

  • Tanguy Damart
  • Werner Van Geit
  • Henry Markram

A bio-inspired approach for the spectrum allocation problem in IoT networks

  • Jesús A. Gómez-Avilés
  • Ángel G. Andrade
  • Anabel Martínez-Vargas

A surrogate model using deep neural networks for optimal oil skimmer assignment

  • Hye-Jin Kim
  • Yong-Hyuk Kim

Usage of a genetic algorithm for optimizing stock usage

  • Mateus Interciso
  • Plínio Barrio Garcia

Automatic evolutionary learning of composite models with knowledge enrichment

  • Anna V. Kalyuzhnaya
  • Nikolay O. Nikitin
  • Pavel Vychuzhanin
  • Alexander Hvatov
  • Alexander Boukhanovsky

An RTS-based algorithm for noisy optimization by strategic sample accumulation

  • Jeongmin Kim
  • Kwang Ryel Ryu

Teng-Yue algorithm: a novel metaheuristic search method for fast cancer classification

  • Tengyue Li
  • Simon Fong
  • Antonio J. Tallón-Ballesteros

Constraint handling in genotype to phenotype mapping and genetic operators for project staffing

  • Soo Ling Lim
  • Yi Kuo
  • Peter J. Bentley

Antimander: open source detection of gerrymandering though multi-objective evolutionary algorithms

  • Joel Simon
  • Joel Lehman

Towards improvement of SUNA in multiplexers with preliminary results of simple logic gate neuron variation

  • Anh Due Ta
  • Danilo Vasconcellos Vargas

Quality enhancement of stochastic feature subset selection via genetic algorithms. Assessment in bioinformatics data sets

  • Antonio J. Tallón-Ballesteros
  • Tengyue Li
  • Simon Fong

On the order of variables for multitasking optimization

  • Lei Wang
  • Qian Sun
  • Qingzheng Xu
  • Balin Tian
  • Wei Li

An effective variable transfer strategy in multitasking optimization

  • Qingzheng Xu
  • Balin Tian
  • Lei Wang
  • Qian Sun
  • Feng Zou

On the co-authorship network in evolutionary computation

  • Dong-Pil Yu
  • Yong-Hyuk Kim

TUTORIAL SESSION: Introductory tutorials

Evolutionary computation: a unified approach

  • Kenneth De Jong

Evolutionary multi-objective optimization: past, present and future

  • Kalyanmoy Deb

A gentle introduction to theory (for non-theoreticians)

  • Benjamin Doerr

Neuroevolution for deep reinforcement learning problems

  • David Ha

Evolutionary many-objective optimization

  • Hisao Ishibuchi
  • Hiroyuki Sato

Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2020

  • Per Kristian Lehrexwid
  • Pietro S. Oliveto

Evolution of neural networks

  • Risto Miikkulainen

Genetic programming: a tutorial introduction

  • Una-May O'Reilly
  • Erik Hemberg

Representations for evolutionary algorithms

  • Franz Rothlauf

Introductory mathematical programming for EC

  • Ofer M. Shir

Learning classifier systems: from principles to modern systems

  • Anthony Stein
  • Masaya Nakata

Model-based evolutionary algorithms: GECCO 2020 tutorial

  • Dirk Thierens
  • Peter A. N. Bosman

Evolutionary computation and games

  • Julian Togelius
  • Sebastian Risi
  • Georgios N. Yannakakis

Hyper-heuristics tutorial

  • Daniel R. Tauritz
  • John Woodward

TUTORIAL SESSION: Advanced tutorials

Design principles for matrix adaptation evolution strategies

  • Hans-Georg Beyer

Quality-diversity optimisation

  • Antoine Cully
  • Jean-Baptiste Mouret
  • Stéphane Doncieux

Statistical analyses for meta-heuristic stochastic optimization algorithms: GECCO 2020 tutorial

  • Tome Eftimov
  • Peter Korošec

Recent advances in particle swarm optimization analysis and understanding

  • AP Engelbrecht
  • CW Cleghorn

Visualization in multiobjective optimization

  • Bogdan Filipič
  • Tea Tušar

Genetic improvement: taking real-world source code and improving it using genetic programming

  • Sæmundur Ó. Haraldsson
  • John R. Woodward
  • Markus Wagner

Solving complex problems with coevolutionary algorithms

  • Krzysztof Krawiec
  • Malcolm Heywood

Decomposition multi-objective optimisation: current developments and future opportunities

  • Ke Li
  • Qingfu Zhang
  • Saúl Zapotecas

Semantic genetic programming

  • Alberto Moraglio
  • Krzysztof Krawiec

Evolutionary computation for digital art

  • Aneta Neumann
  • Frank Neumann

Dynamic control parameter choices in evolutionary computation: GECCO 2020 tutorial

  • Gregor Papa
  • Carola Doerr

Sequential experimentation by evolutionary algorithms

  • Ofer M. Shir
  • Thomas Bäck

Theory and practice of population diversity in evolutionary computation

  • Dirk Sudholt
  • Giovanni Squillero

Fitness landscape analysis to understand and predict algorithm performance for single- and multi-objective optimization

  • Bilel Derbel
  • Sébastien Verel

Benchmarking and analyzing iterative optimization heuristics with IOHprofiler

  • Hao Wang
  • Carola Doerr
  • Ofer M. Shir
  • Thomas Bäck

A hands-on guide to distributed computing paradigms for evolutionary computation

  • Rui Wang
  • Jiale Zhi

TUTORIAL SESSION: Specialized tutorials

Automated algorithm configuration and design

  • Manuel López-Ibáñez
  • Thomas Stützle

Evolutionary computer vision

  • Dr. Gustavo Olague

Search based software engineering: challenges, opportunities and recent applications

  • Ali Ouni

Evolutionary computation and machine learning in cryptology

  • Stjepan Picek
  • Domagoj Jakobovic


  • Lee Spector

Evolutionary algorithms and machine learning: Synergies, Challenges and Opportunities

  • Giovanni Squillero
  • Alberto Tonda

Addressing ethical challenges within evolutionary computation applications: GECCO 2020 tutorial

  • Jim Torresen

Evolutionary algorithms in biomedical data mining: challenges, solutions, and frontiers

  • Ryan J. Urbanowicz
  • Moshe Sipper

Theory of estimation-of-distribution algorithms

  • Carsten Witt

Evolutionary computation for feature selection and feature construction

  • Bing Xue
  • Mengjie Zhang

Swarm intelligence in cybersecurity

  • Ivan Zelinka
  • Roman Šenkeřík

Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition

  • Mengjie Zhang
  • Stefano Cagnoni

WORKSHOP SESSION: Workshop evolutionary many-objective optimization

Preliminary study of adaptive grid-based decomposition on many-objective evolutionary optimization

  • Kensuke Kano
  • Tomoaki Takagi
  • Keiki Takadama
  • Hiroyuki Sato

WORKSHOP SESSION: Workshop the evolution of robots for the real world

Path towards multilevel evolution of robots

  • Shelvin Chand
  • David Howard

If it evolves it needs to learn

  • A. E. Eiben
  • Emma Hart

Automatically designing the behaviours of falling paper: the emergence of non-trivial behaviours via interaction with the physical world

  • Toby Howison
  • Fumiya Iida

Evolutionary stress factors for adaptable robot 'personalities'

  • Edmund R. Hunt

Reusability vs morphological space in physical robot evolution

  • Rodrigo Moreno
  • Andres Faina

Real world morphological evolution is feasible

  • Tønnes F. Nygaard
  • David Howard
  • Kyrre Glette

WORKSHOP SESSION: Workshop industrial applications of metaheuristics

A pareto front-based metric to identify major bitcoin networks influencers

  • Jonathan Gillett
  • Shahryar Rahnamayan
  • Masoud Makrehchi
  • Azam Asilian Bidgoli

A benchmark of recent population-based metaheuristic algorithms for multi-layer neural network training

  • Seyed Jalaleddin Mousavirad
  • Gerald Schaefer
  • Seyed Mohammad Jafar Jalali
  • Iakov Korovin

Scheduling unrelated parallel machines with family setups and resource constraints to minimize total tardiness

  • Júlio C. S. N. Pinheiro
  • José Elias C. Arroyo
  • Lucas Batista Fialho

WORKSHOP SESSION: Workshop swarm intelligence algorithms: Foundations, perspectives and challenges

A modular hybridization of particle swarm optimization and differential evolution

  • Rick Boks
  • Hao Wang
  • Thomas Bäck

Discrete self organizing algorithm for pollution vehicle routing problem

  • Donald Davendra
  • Magdalena Bialic-Davendra

gBeam-ACO: a greedy and faster variant of Beam-ACO

  • Jeff Hajewski
  • Suely Oliveira
  • David E. Stewart
  • Laura Weiler

Self-organizing migrating algorithm with clustering-aided migration

  • Tomas Kadavy
  • Michal Pluhacek
  • Adam Viktorin
  • Roman Senkerik

Colour quantisation using self-organizing migrating algorithm

  • Seyed Jalaleddin Mousavirad
  • Gerald Schaefer
  • Iakov Korovin

High-dimensional multi-level image thresholding using self-organizing migrating algorithm

  • Seyed Jalaleddin Mousavirad
  • Gerald Schaefer
  • Iakov Korovin

Archive-based swarms

  • Nishant Rodrigues
  • Chilukuri Mohan

Ensemble of strategies and perturbation parameter based SOMA for optimal stabilization of chaotic oscillations

  • Roman Senkerik
  • Tomas Kadavy
  • Adam Viktorin
  • Michal Pluhacek

Applications of swarm intelligence algorithms countering the cyber threats

  • Thanh Cong Truong
  • Tan-Phuoc Huynh
  • Ivan Zelinka

WORKSHOP SESSION: Workshop decomposition techniques in evolutionary optimization

Incremental lattice design of weight vector set

  • Tomoaki Takagi
  • Keiki Takadama
  • Hiroyuki Sato

Multi-objective optimization in the agile software project scheduling using decomposition

  • Saúl Zapotecas-Martínez
  • Abel García-Nájera
  • Humberto Cervantes

WORKSHOP SESSION: Workshop genetic and evolutionary computation in defense, security, and risk management

Adversarial threats to large satellite networks (ATLAS-N): a coevolutionary approach based on flipit

  • Jay Patel
  • Dhathri H. Somavarapu
  • Deacon Seals
  • Daniel R. Tauritz
  • Davide Guzzetti

Using evolutionary algorithms and pareto ranking to identify secure virtual local area networks

  • Alina Pacheco Rodríguez
  • Errin W. Fulp
  • David J. John
  • Jinku Cui

Delivering diverse web server configuration in a moving target defense using evolutionary algorithms

  • Ernesto Serrano-Collado
  • Mario García-Valdez
  • Juan-Julián Merelo Guervós

Securing the software defined perimeter with evolutionary co-optimization

  • Michal Shlapentokh-Rothman
  • Erik Hemberg
  • Una-May O'Reilly

Exploring an artificial arms race for malware detection

  • Zachary Wilkins
  • Ibrahim Zincir
  • Nur Zincir-Heywood

WORKSHOP SESSION: Workshop interactive methods

Introducing counterexamples to a robotic agent using clicker training

  • Travis D. DeVault
  • Robert B. Heckendorn
  • Terence Soule

Characteristic analysis of auditory perception and aesthetics in sound composition optimization using revised interactive differential evolution

  • Hayato Shindo
  • Yan Pei

WORKSHOP SESSION: Workshop evolutionary computation software systems

Operon C++: an efficient genetic programming framework for symbolic regression

  • Bogdan Burlacu
  • Gabriel Kronberger
  • Michael Kommenda

Library for evolutionary algorithms in Python (LEAP)

  • Mark A. Coletti
  • Eric O. Scott
  • Jeffrey K. Bassett

Integrating heuristiclab with compilers and interpreters for non-functional code optimization

  • Daniel Dorfmeister
  • Oliver Krauss

GA-lapagos, an open-source c framework including a python-based system for data analysis

  • Peter Jamieson
  • Ricardo Ferreira
  • José Augusto M. Nacif

Implementation matters, also in concurrent evolutionary algorithms

  • Juan-Julián Merelo Guervós
  • Mario García-Valdez
  • Sergio Rojas-Galeano

Open source evolutionary structured optimization

  • Jeremy Rapin
  • Pauline Bennet
  • Emmanuel Centeno
  • Daniel Haziza
  • Antoine Moreau
  • Olivier Teytaud

WORKSHOP SESSION: Workshop real-world applications of continuous and mixed-integer optimization

High-dimensional multi-level maximum variance threshold selection for image segmentation: a benchmark of recent population-based metaheuristic algorithms

  • Seyed Jalaleddin Mousavirad
  • Gerald Schaefer
  • Zahra Movahedi
  • Iakov Korovin

Uncertainty quantification methods for evolutionary optimization under uncertainty

  • Pramudita Satria Palar
  • Koji Shimoyama
  • Lavi Rizki Zuhal

WORKSHOP SESSION: Workshop on surrogate-assisted evolutionary optimisation

What do you mean?: the role of the mean function in bayesian optimisation

  • George De Ath
  • Jonathan E. Fieldsend
  • Richard M. Everson

A surrogate-assisted GA enabling high-throughput ML by optimal feature and discretization selection

  • Johan Garcia

Bayesian methods for multi-objective optimization of a supersonic wing planform

  • Timothy Man Shui Jim
  • Ghifari Adam Faza
  • Pramudita Satria Palar
  • Koji Shimoyama

WORKSHOP SESSION: Workshop evolutionary algorithms for problems with uncertainty

Solution approaches for the dynamic stacking problem

  • Sebastian Raggl
  • Andreas Beham
  • Stefan Wagner
  • Michael Affenzeller

WORKSHOP SESSION: Workshop evolutionary computation for permutation problems

Tabu search and iterated greedy for a flow shop scheduling problem with worker assignment

  • Matheus de Freitas Araujo
  • José Elias C. Arroyo
  • Lucas Batista Fialho

The (1 + (λ, λ)) genetic algorithm for permutations

  • Anton Bassin
  • Maxim Buzdalov

An experimental evaluation of the algebraic differential evolution algorithm on the single row facility layout problem

  • Gabriele Di Bari
  • Marco Baioletti
  • Valentino Santucci

On the solvability of routing multiple point-to-point paths in manhattan meshes

  • Reitze Jansen
  • Yannick Vinkesteijn
  • Daan van den Berg

dMFEA-II: An adaptive multifactorial evolutionary algorithm for permutation-based discrete optimization problems

  • Eneko Osaba
  • Aritz D. Martinez
  • Akemi Galvez
  • Andres Iglesias
  • Javier Del Ser

Monte carlo tree search on perfect rectangle packing problem instances

  • Igor Pejic
  • Daan van den Berg

Gradient search in the space of permutations: an application for the linear ordering problem

  • Valentino Santucci
  • Josu Ceberio
  • Marco Baioletti

WORKSHOP SESSION: Workshop parallel and distributed evolutionary inspired methods

Exploiting multi-objective parallel extremal optimization features in dynamic load balancing

  • Ivanoe De Falco
  • Eryk Laskowski
  • Richard Olejnik
  • Umberto Scafuri
  • Ernesto Tarantino
  • Marek Tudruj

cMOGA/D: a novel cellular GA based on decomposition to tackle constrained multiobjetive problems

  • Cosijopii Garcia-Garcia
  • María-Guadalupe Martínez-Peñaloza
  • Alicia Morales-Reyes

An evolutionary approach for constructing multi-stage classifiers

  • Nolan H. Hamilton
  • Errin W. Fulp

A parallel two-stage genetic algorithm for route planning

  • H. David Mathias
  • Samantha S. Foley

ExaEvo: topological optimization and scalability of evolutionary algorithms

  • Ian Bradley Morgan
  • Daniel R. Tauritz

WORKSHOP SESSION: Workshop international workshop on learning classifier systems

An adaption mechanism for the error threshold of XCSF

  • Tim Hansmeier
  • Paul Kaufmann
  • Marco Platzner

Investigating exploration techniques for ACS in discretized real-valued environments

  • Norbert Kozlowski
  • Olgierd Unold

PEPACS: integrating probability-enhanced predictions to ACS2

  • Romain Orhand
  • Anne Jeannin-Girardon
  • Pierre Parrend
  • Pierre Collet

An overview of LCS research from IWLCS 2019 to 2020

  • David Pätzel
  • Anthony Stein
  • Masaya Nakata

Generic approaches for parallel rule matching in learning classifier systems

  • Lukas Rosenbauer
  • Anthony Stein
  • Jörg Hähner

XCS as a reinforcement learning approach to automatic test case prioritization

  • Lukas Rosenbauer
  • Anthony Stein
  • Roland Maier
  • David Pätzel
  • Jörg Hähner

Learning classifier systems: appreciating the lateralized approach

  • Abubakar Siddique
  • Will N. Browne
  • Gina M. Grimshaw

A scikit-learn compatible learning classifier system

  • Robert F. Zhang
  • Ryan J. Urbanowicz

WORKSHOP SESSION: Workshop neuroevolution at work

Multi-objective evolutionary GAN

  • Marco Baioletti
  • Carlos Artemio Coello Coello
  • Gabriele Di Bari
  • Valentina Poggioni

Learning to walk - reward relevance within an enhanced neuroevolution approach

  • I. Colucci
  • G. Pellegrino
  • A. Della Cioppa
  • A. Marcelli

Mutational puissance assisted neuroevolution

  • Divya D. Kulkarni
  • Shivashankar B. Nair

GEVO-ML: a proposal for optimizing ML code with evolutionary computation

  • Jhe-Yu Liou
  • Xiaodong Wang
  • Stephanie Forrest
  • Carole-Jean Wu

Neuro-evolution using game-driven cultural algorithms

  • Faisal Waris
  • Robert Reynolds

WORKSHOP SESSION: Workshop visualisation methods in genetic and evolutionary computation

Using pagerank to uncover patterns in search behavior induced by the bit flip operator

  • Thomas M. Green
  • Timothy L. Andersen

Visual mapping of multi-objective optimization problems and evolutionary algorithms

  • Kohei Yamamoto
  • Tomoaki Takagi
  • Keiki Takadama
  • Hiroyuki Sato

WORKSHOP SESSION: Workshop evolutionary computation for the automated design of algorithms

On the sensitivity analysis of cartesian genetic programming hyper-heuristic

  • Luis Filipe de Araujo Pessoa
  • Bernd Hellingrath
  • Fernando B. de Lima Neto

The automated design of local optimizers for memetic algorithms employing supportive coevolution

  • Nathaniel R. Kamrath
  • Aaron Scott Pope
  • Daniel R. Tauritz

Time-dependent automatic parameter configuration of a local search algorithm

  • Weerapan Sae-Dan
  • Marie-Eléonore Kessaci
  • Nadarajen Veerapen
  • Laetitia Jourdan

Dynamic primitive granularity control: an exploration of unique design considerations

  • Braden N. Tisdale
  • Aaron Scott Pope
  • Daniel R. Tauritz

WORKSHOP SESSION: Workshop good benchmarking practices for evolutionary computation

A benchmark with facile adjustment of difficulty for many-objective genetic programming and its reference set

  • Makoto Ohki

WORKSHOP SESSION: Workshop genetic improvement

An annotated dataset of stack overflow post edits

  • Sebastian Baltes
  • Markus Wagner

Genetic improvement of software efficiency: the curse of fitness estimation

  • Mahmoud A. Bokhari
  • Markus Wagner
  • Brad Alexander

Evolving sqrt into 1/x via software data maintenance

  • W. B. Langdon
  • Oliver Krauss

Tuning genetic algorithm parameters using design of experiments

  • Mohsen Mosayebi
  • Manbir Sodhi

Optimising the fit of stack overflow code snippets into existing code

  • Brittany Reid
  • Christoph Treude
  • Markus Wagner