Jakob Bossek

Orcid: 0000-0002-4121-4668

Affiliations:
  • RWTH Aachen University, Aachen, Germany


According to our database1, Jakob Bossek authored at least 64 papers between 2012 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Do additional target points speed up evolutionary algorithms?
Theor. Comput. Sci., March, 2023

A study on the effects of normalized TSP features for automated algorithm selection.
Theor. Comput. Sci., 2023

On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem.
CoRR, 2023

On the Impact of Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem.
CoRR, 2023

Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP.
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.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Runtime Analysis of Quality Diversity Algorithms.
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.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022
Co-evolutionary Diversity Optimisation for the Traveling Thief Problem.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems.
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.
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.
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.
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.
Algorithmica, 2021

Exact Counting and Sampling of Optima for the Knapsack Problem.
Proceedings of the Learning and Intelligent Optimization - 15th International Conference, 2021

Entropy-based evolutionary diversity optimisation for the traveling salesperson problem.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Diversifying greedy sampling and evolutionary diversity optimisation for constrained monotone submodular functions.
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.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Generating instances with performance differences for more than just two algorithms.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

Evolutionary diversity optimization and the minimum spanning tree problem.
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.
Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

On the potential of normalized TSP features for automated algorithm selection.
Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

Do additional optima speed up evolutionary algorithms?
Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

2020
Computing Diverse Sets of Solutions for Monotone Submodular Optimisation Problems.
CoRR, 2020

Benchmarking in Optimization: Best Practice and Open Issues.
CoRR, 2020

Initial Design Strategies and their Effects on Sequential Model-Based Optimization.
CoRR, 2020

A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms.
Appl. Soft Comput., 2020

Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.
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.
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020

Evolving Sampling Strategies for One-Shot Optimization Tasks.
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.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Evolving diverse sets of tours for the travelling salesperson problem.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Dynamic bi-objective routing of multiple vehicles.
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.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

The node weight dependent traveling salesperson problem: approximation algorithms and randomized search heuristics.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

More effective randomized search heuristics for graph coloring through dynamic optimization.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

Towards Decision Support in Dynamic Bi-Objective Vehicle Routing.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019
OpenML: An R package to connect to the machine learning platform OpenML.
Comput. Stat., 2019

One-Shot Decision-Making with and without Surrogates.
CoRR, 2019

On the benefits of biased edge-exchange mutation for the multi-criteria spanning tree problem.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Runtime analysis of randomized search heuristics for dynamic graph coloring.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Time complexity analysis of RLS and (1 + 1) EA for the edge coloring problem.
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.
Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2019

Bi-objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm.
Proceedings of the Evolutionary Multi-Criterion Optimization, 2019

2018
grapherator: A Modular Multi-Step Graph Generator.
J. Open Source Softw., 2018

Leveraging TSP Solver Complementarity through Machine Learning.
Evol. Comput., 2018

Multi-objective Performance Measurement: Alternatives to PAR10 and Expected Running Time.
Proceedings of the Learning and Intelligent Optimization - 12th International Conference, 2018

Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems.
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.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

Local search effects in bi-objective orienteering.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018

Performance assessment of multi-objective evolutionary algorithms with the R package ecr.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

2017
smoof: Single- and Multi-Objective Optimization Test Functions.
R J., 2017

mcMST: A Toolbox for the Multi-Criteria Minimum Spanning Tree Problem.
J. Open Source Softw., 2017

OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML.
CoRR, 2017

An extended mutation-based priority-rule integration concept for multi-objective machine scheduling.
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.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

ecr 2.0: a modular framework for evolutionary computation in R.
Proceedings of the Genetic and Evolutionary Computation Conference, 2017

2016
Evolving Instances for Maximizing Performance Differences of State-of-the-Art Inexact TSP Solvers.
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.
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.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2013
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem.
Ann. Math. Artif. Intell., 2013

2012
Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness.
Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012


  Loading...