174 citations · 389 across the 26 of their papers we have counts for
10 papers · 1 filter
To Repair or Not to Repair? Investigating the Importance of AB-Cycles for the State-of-the-Art TSP Heuristic EAX
Jonathan Heins, Darrell Whitley, Pascal Kerschke
The Edge Assembly Crossover (EAX) algorithm is the state-of-the-art heuristic for solving the Traveling Salesperson Problem (TSP). It regularly outperforms other methods, such as t…
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization
Konstantin Dietrich, Diederick Vermetten, Carola Doerr +1
The recently proposed MA-BBOB function generator provides a way to create numerical black-box benchmark problems based on the well-established BBOB suite. Initial studies on this g…
To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
Simultaneously visualizing the decision and objective space of continuous multi-objective optimization problems (MOPs) recently provided key contributions in understanding the stru…
Multiobjectivization of Local Search: Single-Objective Optimization Benefits From Multi-Objective Gradient Descent
Vera Steinhoff, Pascal Kerschke, Pelin Aspar +2
Multimodality is one of the biggest difficulties for optimization as local optima are often preventing algorithms from making progress. This does not only challenge local strategie…
Benchmarking in Optimization: Best Practice and Open Issues
Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg +14
This survey compiles ideas and recommendations from more than a dozen researchers with different backgrounds and from different institutes around the world. Promoting best practice…
Empirical Study on the Benefits of Multiobjectivization for Solving Single-Objective Problems
Vera Steinhoff, Pascal Kerschke, Christian Grimme
When dealing with continuous single-objective problems, multimodality poses one of the biggest difficulties for global optimization. Local optima are often preventing algorithms fr…
One PLOT to Show Them All: Visualization of Efficient Sets in Multi-Objective Landscapes
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
Visualization techniques for the decision space of continuous multi-objective optimization problems (MOPs) are rather scarce in research. For long, all techniques focused on global…
Initial Design Strategies and their Effects on Sequential Model-Based Optimization
Jakob Bossek, Carola Doerr, Pascal Kerschke
Sequential model-based optimization (SMBO) approaches are algorithms for solving problems that require computationally or otherwise expensive function evaluations. The key design p…
The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics
Jakob Bossek, Katrin Casel, Pascal Kerschke +1
Several important optimization problems in the area of vehicle routing can be seen as a variant of the classical Traveling Salesperson Problem (TSP). In the area of evolutionary co…
One-Shot Decision-Making with and without Surrogates
Jakob Bossek, Pascal Kerschke, Aneta Neumann +2
One-shot decision making is required in situations in which we can evaluate a fixed number of solution candidates but do not have any possibility for further, adaptive sampling. Su…