default search action
Jakob Bossek
Person information
- affiliation: RWTH Aachen University, Aachen, Germany
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j11]Jakob Bossek, Christian Grimme:
On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem. Evol. Comput. 32(2): 143-175 (2024) - [c49]Jakob Bossek
, Christian Grimme
Generalised Kruskal Mutation for the Multi-Objective Minimum Spanning Tree Problem. GECCO 2024 - [c48]Marcus Schmidbauer
Guiding Quality Diversity on Monotone Submodular Functions: Customising the Feature Space by Adding Boolean Conjunctions. GECCO 2024 - 2023
- [j10]Jonathan Heins
A study on the effects of normalized TSP features for automated algorithm selection. Theor. Comput. Sci. 940(Part): 123-145 (2023) - [j9]Jakob Bossek
Do additional target points speed up evolutionary algorithms? Theor. Comput. Sci. 950: 113757 (2023) - [c47]Jakob Bossek
On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. GECCO 2023: 248-256 - [c46]Alejandro Marrero
Generating diverse and discriminatory knapsack instances by searching for novelty in variable dimensions of feature-space. GECCO 2023: 312-320 - [c45]Jakob Bossek
Runtime Analysis of Quality Diversity Algorithms. GECCO 2023: 1546-1554 - [c44]Moritz Vinzent Seiler, Jeroen Rook
Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP. SSCI 2023: 361-368 - [i26]Jakob Bossek, Aneta Neumann, Frank Neumann:
On the Impact of Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem. CoRR abs/2305.18955 (2023) - [i25]Jakob Bossek, Dirk Sudholt:
Runtime Analysis of Quality Diversity Algorithms. CoRR abs/2305.18966 (2023) - [i24]Jakob Bossek, Christian Grimme:
On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem. CoRR abs/2306.00222 (2023) - 2022
- [c43]Jakob Bossek, Frank Neumann:
Exploring the feature space of TSP instances using quality diversity. GECCO 2022: 186-194 - [c42]Jeroen Rook
On the potential of automated algorithm configuration on multi-modal multi-objective optimization problems. GECCO Companion 2022: 356-359 - [c41]Jakob Bossek, Aneta Neumann, Frank Neumann:
Evolutionary diversity optimization for combinatorial optimization: tutorial at GECCO'22, Boston, USA. GECCO Companion 2022: 824-842 - [c40]Jonathan Heins
BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. PPSN (1) 2022: 192-206 - [c39]Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann:
Co-evolutionary Diversity Optimisation for the Traveling Thief Problem. PPSN (1) 2022: 237-249 - [i23]Jakob Bossek, Frank Neumann:
Exploring the Feature Space of TSP Instances Using Quality Diversity. CoRR abs/2202.02077 (2022) - [i22]Adel Nikfarjam, Aneta Neumann, Jakob Bossek, Frank Neumann:
Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. CoRR abs/2207.14036 (2022) - 2021
- [j8]Jakob Bossek
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. Algorithmica 83(10): 3148-3179 (2021) - [c38]Jonathan Heins
On the potential of normalized TSP features for automated algorithm selection. FOGA 2021: 7:1-7:15 - [c37]Jakob Bossek
Do additional optima speed up evolutionary algorithms? FOGA 2021: 8:1-8:11 - [c36]Adel Nikfarjam, Jakob Bossek, Aneta Neumann
Computing diverse sets of high quality TSP tours by EAX-based evolutionary diversity optimisation. FOGA 2021: 9:1-9:11 - [c35]Jakob Bossek
Evolutionary diversity optimization and the minimum spanning tree problem. GECCO 2021: 198-206 - [c34]Aneta Neumann
Diversifying greedy sampling and evolutionary diversity optimisation for constrained monotone submodular functions. GECCO 2021: 261-269 - [c33]Jakob Bossek, Aneta Neumann
Breeding diverse packings for the knapsack problem by means of diversity-tailored evolutionary algorithms. GECCO 2021: 556-564 - [c32]Adel Nikfarjam, Jakob Bossek
Entropy-based evolutionary diversity optimisation for the traveling salesperson problem. GECCO 2021: 600-608 - [c31]Jakob Bossek
Generating instances with performance differences for more than just two algorithms. GECCO Companion 2021: 1423-1432 - [c30]Jakob Bossek
Exact Counting and Sampling of Optima for the Knapsack Problem. LION 2021: 40-54 - [i21]Jakob Bossek, Aneta Neumann, Frank Neumann:
Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. CoRR abs/2104.13133 (2021) - [i20]Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann:
Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem. CoRR abs/2104.13538 (2021) - [i19]Jakob Bossek, Markus Wagner:
Generating Instances with Performance Differences for More Than Just Two Algorithms. CoRR abs/2104.14275 (2021) - [i18]Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt:
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. CoRR abs/2105.12525 (2021) - [i17]Jakob Bossek, Aneta Neumann, Frank Neumann:
Exact Counting and Sampling of Optima for the Knapsack Problem. CoRR abs/2106.07412 (2021) - [i16]Adel Nikfarjam, Jakob Bossek, Aneta Neumann, Frank Neumann:
Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation. CoRR abs/2108.05005 (2021) - 2020
- [j7]Jakob Bossek
A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms. Appl. Soft Comput. 88: 105901 (2020) - [c29]Jakob Bossek
Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. CEC 2020: 1-8 - [c28]Jakob Bossek
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. CEC 2020: 1-8 - [c27]Jakob Bossek
Dynamic bi-objective routing of multiple vehicles. GECCO 2020: 166-174 - [c26]Vahid Roostapour, Jakob Bossek, Frank Neumann:
Runtime analysis of evolutionary algorithms with biased mutation for the multi-objective minimum spanning tree problem. GECCO 2020: 551-559 - [c25]Anh Viet Do
Evolving diverse sets of tours for the travelling salesperson problem. GECCO 2020: 681-689 - [c24]Jakob Bossek, Carola Doerr
Initial design strategies and their effects on sequential model-based optimization: an exploratory case study based on BBOB. GECCO 2020: 778-786 - [c23]Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt:
More effective randomized search heuristics for graph coloring through dynamic optimization. GECCO 2020: 1277-1285 - [c22]Jakob Bossek, Katrin Casel, Pascal Kerschke
The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics. GECCO 2020: 1286-1294 - [c21]Moritz Seiler, Janina Pohl, Jakob Bossek, Pascal Kerschke
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. PPSN (1) 2020: 48-64 - [c20]Jakob Bossek, Carola Doerr
Evolving Sampling Strategies for One-Shot Optimization Tasks. PPSN (1) 2020: 111-124 - [c19]Jakob Bossek, Aneta Neumann
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions. PPSN (1) 2020: 346-359 - [i15]Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neumann:
The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics. CoRR abs/2002.01070 (2020) - [i14]Jakob Bossek, Carola Doerr, Pascal Kerschke:
Initial Design Strategies and their Effects on Sequential Model-Based Optimization. CoRR abs/2003.13826 (2020) - [i13]Anh Viet Do, Jakob Bossek, Aneta Neumann, Frank Neumann:
Evolving Diverse Sets of Tours for the Travelling Salesperson Problem. CoRR abs/2004.09188 (2020) - [i12]Vahid Roostapour, Jakob Bossek, Frank Neumann:
Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem. CoRR abs/2004.10424 (2020) - [i11]Jakob Bossek, Pascal Kerschke, Heike Trautmann:
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection. CoRR abs/2005.13289 (2020) - [i10]Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt:
More Effective Randomized Search Heuristics for Graph Coloring Through Dynamic Optimization. CoRR abs/2005.13825 (2020) - [i9]Jakob Bossek, Christian Grimme, Günter Rudolph, Heike Trautmann:
Towards Decision Support in Dynamic Bi-Objective Vehicle Routing. CoRR abs/2005.13865 (2020) - [i8]Jakob Bossek, Christian Grimme, Heike Trautmann:
Dynamic Bi-Objective Routing of Multiple Vehicles. CoRR abs/2005.13872 (2020) - [i7]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 abs/2006.03260 (2020) - [i6]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 abs/2006.15968 (2020) - [i5]Thomas Bartz-Beielstein
Benchmarking in Optimization: Best Practice and Open Issues. CoRR abs/2007.03488 (2020) - [i4]Jakob Bossek, Frank Neumann:
Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. CoRR abs/2010.10913 (2020) - [i3]Aneta Neumann, Jakob Bossek, Frank Neumann:
Computing Diverse Sets of Solutions for Monotone Submodular Optimisation Problems. CoRR abs/2010.11486 (2020)
2010 – 2019
- 2019
- [j6]Giuseppe Casalicchio
OpenML: An R package to connect to the machine learning platform OpenML. Comput. Stat. 34(3): 977-991 (2019) - [c18]Jakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, Heike Trautmann:
Bi-objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm. EMO 2019: 516-528 - [c17]Jakob Bossek, Pascal Kerschke
Evolving diverse TSP instances by means of novel and creative mutation operators. FOGA 2019: 58-71 - [c16]Jakob Bossek, Dirk Sudholt:
Time complexity analysis of RLS and (1 + 1) EA for the edge coloring problem. FOGA 2019: 102-115 - [c15]Jakob Bossek, Christian Grimme, Frank Neumann
On the benefits of biased edge-exchange mutation for the multi-criteria spanning tree problem. GECCO 2019: 516-523 - [c14]Jakob Bossek
Runtime analysis of randomized search heuristics for dynamic graph coloring. GECCO 2019: 1443-1451 - [i2]Jakob Bossek, Pascal Kerschke, Aneta Neumann, Frank Neumann, Carola Doerr:
One-Shot Decision-Making with and without Surrogates. CoRR abs/1912.08956 (2019) - 2018
- [j5]Pascal Kerschke
Leveraging TSP Solver Complementarity through Machine Learning. Evol. Comput. 26(4) (2018) - [j4]Jakob Bossek
grapherator: A Modular Multi-Step Graph Generator. J. Open Source Softw. 3(22): 528 (2018) - [c13]Jakob Bossek
Local search effects in bi-objective orienteering. GECCO 2018: 585-592 - [c12]Jakob Bossek
Performance assessment of multi-objective evolutionary algorithms with the R package ecr. GECCO (Companion) 2018: 1350-1356 - [c11]Pascal Kerschke
Parameterization of state-of-the-art performance indicators: a robustness study based on inexact TSP solvers. GECCO (Companion) 2018: 1737-1744 - [c10]Jakob Bossek
Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems. LION 2018: 184-198 - [c9]Jakob Bossek
Multi-objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. LION 2018: 215-219 - 2017
- [j3]Jakob Bossek
mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem. J. Open Source Softw. 2(17): 374 (2017) - [j2]Jakob Bossek
smoof: Single- and Multi-Objective Optimization Test Functions. R J. 9(1): 103 (2017) - [c8]Jakob Bossek
ecr 2.0: a modular framework for evolutionary computation in R. GECCO (Companion) 2017: 1187-1193 - [c7]Jakob Bossek
A pareto-beneficial sub-tree mutation for the multi-criteria minimum spanning tree problem. SSCI 2017: 1-8 - [c6]Jakob Bossek
An extended mutation-based priority-rule integration concept for multi-objective machine scheduling. SSCI 2017: 1-8 - [i1]Giuseppe Casalicchio, Jakob Bossek, Michel Lang
OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML. CoRR abs/1701.01293 (2017) - 2016
- [c5]Jakob Bossek
Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. AI*IA 2016: 3-12 - [c4]Jakob Bossek
Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers. LION 2016: 48-59 - 2015
- [c3]Stephan Meisel, Christian Grimme, Jakob Bossek
Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. GECCO 2015: 425-432 - [c2]Jakob Bossek
Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement. GECCO 2015: 1319-1326 - 2013
- [j1]Olaf Mersmann
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem. Ann. Math. Artif. Intell. 69(2): 151-182 (2013) - 2012
- [c1]Olaf Mersmann
Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. LION 2012: 115-129
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-05 20:22 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: