Jakob Bossek

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 82

Top Topics

Optimisation Problems

Learning Platform

Top Venues

Publications

Jakob Bossek, Christian Grimme
Generalised Kruskal Mutation for the Multi-Objective Minimum Spanning Tree Problem. GECCO (2024)
Jakob Bossek, Christian Grimme
On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem. Evol. Comput. 32 (2) (2024)
Marcus Schmidbauer, Andre Opris, Jakob Bossek, Frank Neumann, Dirk Sudholt
Guiding Quality Diversity on Monotone Submodular Functions: Customising the Feature Space by Adding Boolean Conjunctions. GECCO (2024)
Alejandro Marrero, Eduardo Segredo, Emma Hart, Jakob Bossek, Aneta Neumann
Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space. GECCO (2023)
Jakob Bossek, Dirk Sudholt
Runtime Analysis of Quality Diversity Algorithms. GECCO (2023)
Jakob Bossek, Dirk Sudholt
Runtime Analysis of Quality Diversity Algorithms. CoRR (2023)
Jakob Bossek, Aneta Neumann, Frank Neumann
On the Impact of Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. CoRR (2023)
Jakob Bossek, Dirk Sudholt
Do additional target points speed up evolutionary algorithms? Theor. Comput. Sci. 950 (2023)
Moritz Vinzent Seiler, Jeroen Rook, Jonathan Heins, Oliver Ludger Preuß, Jakob Bossek, Heike Trautmann
Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. SSCI (2023)
Jakob Bossek, Christian Grimme
On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem. CoRR (2023)
Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke
A study on the effects of normalized TSP features for automated algorithm selection. Theor. Comput. Sci. 940 (Part) (2023)
Jakob Bossek, Aneta Neumann, Frank Neumann
On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. GECCO (2023)
Jonathan Heins, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, Heike Trautmann
BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. PPSN (1) (2022)
Jakob Bossek, Aneta Neumann, Frank Neumann
Evolutionary diversity optimization for combinatorial optimization: tutorial at GECCO'22, Boston, USA. GECCO Companion (2022)
Jeroen Rook, Heike Trautmann, Jakob Bossek, Christian Grimme
On the potential of automated algorithm configuration on multi-modal multi-objective optimization problems. GECCO Companion (2022)
Jakob Bossek, Frank Neumann
Exploring the Feature Space of TSP Instances Using Quality Diversity. CoRR (2022)
Jakob Bossek, Frank Neumann
Exploring the feature space of TSP instances using quality diversity. GECCO (2022)
Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann
Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. CoRR (2022)
Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann
Co-evolutionary Diversity Optimisation for the Traveling Thief Problem. PPSN (1) (2022)
Jonathan Heins, Jakob Bossek, Janina Pohl, Moritz Seiler, Heike Trautmann, Pascal Kerschke
On the potential of normalized TSP features for automated algorithm selection. FOGA (2021)
Jakob Bossek, Aneta Neumann, Frank Neumann
Exact Counting and Sampling of Optima for the Knapsack Problem. CoRR (2021)
Aneta Neumann, Jakob Bossek, Frank Neumann
Diversifying greedy sampling and evolutionary diversity optimisation for constrained monotone submodular functions. GECCO (2021)
Jakob Bossek, Aneta Neumann, Frank Neumann
Exact Counting and Sampling of Optima for the Knapsack Problem. LION (2021)
Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann
Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. CoRR (2021)
Jakob Bossek, Aneta Neumann, Frank Neumann
Breeding diverse packings for the knapsack problem by means of diversity-tailored evolutionary algorithms. GECCO (2021)
Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann
Computing diverse sets of high quality TSP tours by EAX-based evolutionary diversity optimisation. FOGA (2021)
Jakob Bossek, Frank Neumann
Evolutionary diversity optimization and the minimum spanning tree problem. GECCO (2021)
Jakob Bossek, Markus Wagner
Generating instances with performance differences for more than just two algorithms. GECCO Companion (2021)
Jakob Bossek, Aneta Neumann, Frank Neumann
Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. CoRR (2021)
Jakob Bossek, Dirk Sudholt
Do additional optima speed up evolutionary algorithms? FOGA (2021)
Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann
Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation. CoRR (2021)
Jakob Bossek, Markus Wagner
Generating Instances with Performance Differences for More Than Just Two Algorithms. CoRR (2021)
Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. Algorithmica 83 (10) (2021)
Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann
Entropy-based evolutionary diversity optimisation for the traveling salesperson problem. GECCO (2021)
Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. CoRR (2021)
Jakob Bossek, Pascal Kerschke, Heike Trautmann
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. CoRR (2020)
Vahid Roostapour, Jakob Bossek, Frank Neumann
Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem. CoRR (2020)
Jakob Bossek, Christian Grimme, Günter Rudolph, Heike Trautmann
Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. CoRR (2020)
Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. CoRR (2020)
Anh Viet Do, Jakob Bossek, Aneta Neumann, Frank Neumann
Evolving Diverse Sets of Tours for the Travelling Salesperson Problem. CoRR (2020)
Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann
The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics. CoRR (2020)
Jakob Bossek, Christian Grimme, Heike Trautmann
Dynamic bi-objective routing of multiple vehicles. GECCO (2020)
Jakob Bossek, Aneta Neumann, Frank Neumann
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions. PPSN (1) (2020)
Jakob Bossek, Christian Grimme, Günter Rudolph, Heike Trautmann
Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. CEC (2020)
Jakob Bossek, Pascal Kerschke, Heike Trautmann
A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Appl. Soft Comput. 88 (2020)
Jakob Bossek, Carola Doerr, Pascal Kerschke
Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB. GECCO (2020)
Aneta Neumann, Jakob Bossek, Frank Neumann
Computing Diverse Sets of Solutions for Monotone Submodular Optimisation Problems. CoRR (2020)
Anh Viet Do, Jakob Bossek, Aneta Neumann, Frank Neumann
Evolving diverse sets of tours for the travelling salesperson problem. GECCO (2020)
Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt
More Effective Randomized Search Heuristics for Graph Coloring Through Dynamic Optimization. CoRR (2020)
Jakob Bossek, Christian Grimme, Heike Trautmann
Dynamic Bi-Objective Routing of Multiple Vehicles. CoRR (2020)
Jakob Bossek, Pascal Kerschke, Heike Trautmann
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. CEC (2020)
Jakob Bossek, Carola Doerr, Pascal Kerschke, Aneta Neumann, Frank Neumann
Evolving Sampling Strategies for One-Shot Optimization Tasks. PPSN (1) (2020)
Jakob Bossek, Carola Doerr, Pascal Kerschke
Initial Design Strategies and their Effects on Sequential Model-Based Optimization. CoRR (2020)
Jakob Bossek, Aneta Neumann, Frank Neumann
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions. CoRR (2020)
Vahid Roostapour, Jakob Bossek, Frank Neumann
Runtime analysis of evolutionary algorithms with biased mutation for the multi-objective minimum spanning tree problem. GECCO (2020)
Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt
More effective randomized search heuristics for graph coloring through dynamic optimization. GECCO (2020)
Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke, Heike Trautmann
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. PPSN (1) (2020)
Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann
The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics. GECCO (2020)
Jakob Bossek, Frank Neumann
Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. CoRR (2020)
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
Benchmarking in Optimization: Best Practice and Open Issues. CoRR (2020)
Jakob Bossek, Pascal Kerschke, Aneta Neumann, Markus Wagner, Frank Neumann, Heike Trautmann
Evolving diverse TSP instances by means of novel and creative mutation operators. FOGA (2019)
Jakob Bossek, Dirk Sudholt
Time complexity analysis of RLS and (1 + 1) EA for the edge coloring problem. FOGA (2019)
Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt
Runtime analysis of randomized search heuristics for dynamic graph coloring. GECCO (2019)
Jakob Bossek, Christian Grimme, Frank Neumann
On the benefits of biased edge-exchange mutation for the multi-criteria spanning tree problem. GECCO (2019)
Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl
OpenML: An R package to connect to the machine learning platform OpenML. Comput. Stat. 34 (3) (2019)
Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr
One-Shot Decision-Making with and without Surrogates. CoRR (2019)
Jakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, Heike Trautmann
Bi-objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm. EMO (2019)
Pascal Kerschke, Lars Kotthoff, Jakob Bossek, Holger H. Hoos, Heike Trautmann
Leveraging TSP Solver Complementarity through Machine Learning. Evol. Comput. 26 (4) (2018)
Jakob Bossek
Performance assessment of multi-objective evolutionary algorithms with the R package ecr. GECCO (Companion) (2018)
Pascal Kerschke, Jakob Bossek, Heike Trautmann
Parameterization of state-of-the-art performance indicators: a robustness study based on inexact TSP solvers. GECCO (Companion) (2018)
Jakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, Heike Trautmann
Local search effects in bi-objective orienteering. GECCO (2018)
Jakob Bossek, Heike Trautmann
Multi-objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. LION (2018)
Jakob Bossek
grapherator: A Modular Multi-Step Graph Generator. J. Open Source Softw. 3 (22) (2018)
Jakob Bossek, Christian Grimme
Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems. LION (2018)
Giuseppe Casalicchio, Jakob Bossek, Michel Lang, Dominik Kirchhoff, Pascal Kerschke, Benjamin Hofner, Heidi Seibold, Joaquin Vanschoren, Bernd Bischl
OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML. CoRR (2017)
Jakob Bossek
smoof: Single- and Multi-Objective Optimization Test Functions. R J. 9 (1) (2017)
Jakob Bossek, Christian Grimme
A pareto-beneficial sub-tree mutation for the multi-criteria minimum spanning tree problem. SSCI (2017)
Jakob Bossek
mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem. J. Open Source Softw. 2 (17) (2017)
Jakob Bossek, Christian Grimme
An extended mutation-based priority-rule integration concept for multi-objective machine scheduling. SSCI (2017)
Jakob Bossek
ecr 2.0: a modular framework for evolutionary computation in R. GECCO (Companion) (2017)
Jakob Bossek, Heike Trautmann
Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. AI*IA (2016)
Jakob Bossek, Heike Trautmann
Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers. LION (2016)
Stephan Meisel, Christian Grimme, Jakob Bossek, Martin Wölck, Günter Rudolph, Heike Trautmann
Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. GECCO (2015)
Jakob Bossek, Bernd Bischl, Tobias Wagner, Günter Rudolph
Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement. GECCO (2015)
Olaf Mersmann, Bernd Bischl, Heike Trautmann, Markus Wagner, Jakob Bossek, Frank Neumann
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem. Ann. Math. Artif. Intell. 69 (2) (2013)
Olaf Mersmann, Bernd Bischl, Jakob Bossek, Heike Trautmann, Markus Wagner, Frank Neumann
Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. LION (2012)