Jakob Bossek

According to our database, Jakob Bossek authored at least 66 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Runtime Analysis of Quality Diversity Algorithms.

Jakob Bossek, Dirk Sudholt

Algorithmica, October, 2024

On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem.

Jakob Bossek, Christian Grimme

Evol. Comput., 2024

Guiding Quality Diversity on Monotone Submodular Functions: Customising the Feature Space by Adding Boolean Conjunctions.

Marcus Schmidbauer, Andre Opris, Jakob Bossek, Frank Neumann, Dirk Sudholt

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Generalised Kruskal Mutation for the Multi-Objective Minimum Spanning Tree Problem.

Jakob Bossek, Christian Grimme

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

2023

Do additional target points speed up evolutionary algorithms?

Jakob Bossek, Dirk Sudholt

Theor. Comput. Sci., March, 2023

A study on the effects of normalized TSP features for automated algorithm selection.

Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke

Theor. Comput. Sci., 2023

On the Impact of Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem.

Jakob Bossek, Aneta Neumann, Frank Neumann

CoRR, 2023

Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.

Moritz Vinzent Seiler, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, Heike Trautmann

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space.

Alejandro Marrero, Eduardo Segredo, Emma Hart, Jakob Bossek, Aneta Neumann

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem.

Jakob Bossek, Aneta Neumann, Frank Neumann

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

Co-evolutionary Diversity Optimisation for the Traveling Thief Problem.

Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann

Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems.

Jonathan Heins, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, Heike Trautmann

Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

On the potential of automated algorithm configuration on multi-modal multi-objective optimization problems.

Jeroen Rook, Heike Trautmann, Jakob Bossek, Christian Grimme

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Evolutionary diversity optimization for combinatorial optimization: tutorial at GECCO'22, Boston, USA.

Jakob Bossek, Aneta Neumann, Frank Neumann

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Exploring the feature space of TSP instances using quality diversity.

Jakob Bossek, Frank Neumann

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

2021

Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.

Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt

Algorithmica, 2021

Exact Counting and Sampling of Optima for the Knapsack Problem.

Jakob Bossek, Aneta Neumann, Frank Neumann

Proceedings of the Learning and Intelligent Optimization - 15th International Conference, 2021

Entropy-based evolutionary diversity optimisation for the traveling salesperson problem.

Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Diversifying greedy sampling and evolutionary diversity optimisation for constrained monotone submodular functions.

Aneta Neumann, Jakob Bossek, Frank Neumann

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Breeding diverse packings for the knapsack problem by means of diversity-tailored evolutionary algorithms.

Jakob Bossek, Aneta Neumann, Frank Neumann

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Generating instances with performance differences for more than just two algorithms.

Jakob Bossek, Markus Wagner

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Evolutionary diversity optimization and the minimum spanning tree problem.

Jakob Bossek, Frank Neumann

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Computing diverse sets of high quality TSP tours by EAX-based evolutionary diversity optimisation.

Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann

Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

On the potential of normalized TSP features for automated algorithm selection.

Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke

Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

Do additional optima speed up evolutionary algorithms?

Jakob Bossek, Dirk Sudholt

Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

2020

Computing Diverse Sets of Solutions for Monotone Submodular Optimisation Problems.

Aneta Neumann, Jakob Bossek, Frank Neumann

CoRR, 2020

Benchmarking in Optimization: Best Practice and Open Issues.

Thomas Bartz-Beielstein, Carola Doerr, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, Manuel López-Ibáñez, Katherine M. Malan, Jason H. Moore, Boris Naujoks, Patryk Orzechowski, Vanessa Volz, Markus Wagner, Thomas Weise

CoRR, 2020

Initial Design Strategies and their Effects on Sequential Model-Based Optimization.

Jakob Bossek, Carola Doerr, Pascal Kerschke

CoRR, 2020

A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms.

Jakob Bossek, Pascal Kerschke, Heike Trautmann

Appl. Soft Comput., 2020

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.

Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann

Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions.

Jakob Bossek, Aneta Neumann, Frank Neumann

Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

Evolving Sampling Strategies for One-Shot Optimization Tasks.

Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann

Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

Runtime analysis of evolutionary algorithms with biased mutation for the multi-objective minimum spanning tree problem.

Vahid Roostapour, Jakob Bossek, Frank Neumann

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

Evolving diverse sets of tours for the travelling salesperson problem.

Anh Viet Do, Jakob Bossek, Aneta Neumann, Frank Neumann

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

Dynamic bi-objective routing of multiple vehicles.

Jakob Bossek, Christian Grimme, Heike Trautmann

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

Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB.

Jakob Bossek, Carola Doerr, Pascal Kerschke

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

The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics.

Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann

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

More effective randomized search heuristics for graph coloring through dynamic optimization.

Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt

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

Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection.

Jakob Bossek, Pascal Kerschke, Heike Trautmann

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Towards Decision Support in Dynamic Bi-Objective Vehicle Routing.

Jakob Bossek, Christian Grimme, Günter Rudolph, Heike Trautmann

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019

OpenML: An R package to connect to the machine learning platform OpenML.

Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl

Comput. Stat., 2019

One-Shot Decision-Making with and without Surrogates.

Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr

CoRR, 2019

On the benefits of biased edge-exchange mutation for the multi-criteria spanning tree problem.

Jakob Bossek, Christian Grimme, Frank Neumann

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Runtime analysis of randomized search heuristics for dynamic graph coloring.

Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Time complexity analysis of RLS and (1 + 1) EA for the edge coloring problem.

Jakob Bossek, Dirk Sudholt

Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2019

Evolving diverse TSP instances by means of novel and creative mutation operators.

Jakob Bossek, Pascal Kerschke, Aneta Neumann, Markus Wagner, Frank Neumann, Heike Trautmann

Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2019

Bi-objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm.

Jakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, Heike Trautmann

Proceedings of the Evolutionary Multi-Criterion Optimization, 2019

2018

grapherator: A Modular Multi-Step Graph Generator.

Jakob Bossek

J. Open Source Softw., 2018

Leveraging TSP Solver Complementarity through Machine Learning.

Pascal Kerschke, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, Heike Trautmann

Evol. Comput., 2018

Multi-objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.

Jakob Bossek, Heike Trautmann

Proceedings of the Learning and Intelligent Optimization - 12th International Conference, 2018

Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems.

Jakob Bossek, Christian Grimme

Proceedings of the Learning and Intelligent Optimization - 12th International Conference, 2018

Parameterization of state-of-the-art performance indicators: a robustness study based on inexact TSP solvers.

Pascal Kerschke, Jakob Bossek, Heike Trautmann

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

Local search effects in bi-objective orienteering.

Jakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, Heike Trautmann

Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Performance assessment of multi-objective evolutionary algorithms with the R package ecr.

Jakob Bossek

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

2017

smoof: Single- and Multi-Objective Optimization Test Functions.

Jakob Bossek

R J., 2017

mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem.

Jakob Bossek

J. Open Source Softw., 2017

OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML.

Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl

CoRR, 2017

An extended mutation-based priority-rule integration concept for multi-objective machine scheduling.

Jakob Bossek, Christian Grimme

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

A pareto-beneficial sub-tree mutation for the multi-criteria minimum spanning tree problem.

Jakob Bossek, Christian Grimme

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

ecr 2.0: a modular framework for evolutionary computation in R.

Jakob Bossek

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

2016

Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers.

Jakob Bossek, Heike Trautmann

Proceedings of the Learning and Intelligent Optimization - 10th International Conference, 2016

Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference.

Jakob Bossek, Heike Trautmann

Proceedings of the AI*IA 2016: Advances in Artificial Intelligence - XVth International Conference of the Italian Association for Artificial Intelligence, Genova, Italy, November 29, 2016

2015

Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle.

Stephan Meisel, Christian Grimme, Jakob Bossek, Martin Wölck, Günter Rudolph, Heike Trautmann

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement.

Jakob Bossek, Bernd Bischl, Tobias Wagner, Günter Rudolph

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2013

A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem.

Olaf Mersmann, Bernd Bischl, Heike Trautmann, Markus Wagner, Jakob Bossek, Frank Neumann

Ann. Math. Artif. Intell., 2013

2012

Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness.

Olaf Mersmann, Bernd Bischl, Jakob Bossek, Heike Trautmann, Markus Wagner, Frank Neumann

Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012