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05/31/2023
On Single-Objective Sub-Graph-Based Mutation for Solving the Bi-Objective Minimum Spanning Tree Problem
We contribute to the efficient approximation of the Pareto-set for the c...
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05/30/2023
Runtime Analysis of Quality Diversity Algorithms
Quality diversity (QD) is a branch of evolutionary computation that gain...
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05/30/2023
On the Impact of Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem
Evolutionary algorithms have been shown to obtain good solutions for com...
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07/28/2022
Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem
Recently different evolutionary computation approaches have been develop...
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02/04/2022
Exploring the Feature Space of TSP Instances Using Quality Diversity
Generating instances of different properties is key to algorithm selecti...
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08/11/2021
Computing Diverse Sets of High Quality TSP Tours by EAX-Based Evolutionary Diversity Optimisation
Evolutionary algorithms based on edge assembly crossover (EAX) constitut...
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06/14/2021
Exact Counting and Sampling of Optima for the Knapsack Problem
Computing sets of high quality solutions has gained increasing interest ...
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05/26/2021
Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem
We contribute to the theoretical understanding of randomized search heur...
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04/28/2021
Entropy-Based Evolutionary Diversity Optimisation for the Traveling Salesperson Problem
Computing diverse sets of high-quality solutions has gained increasing a...
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04/27/2021
Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms
In practise, it is often desirable to provide the decision-maker with a ...
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10/22/2020
Computing Diverse Sets of Solutions for Monotone Submodular Optimisation Problems
Submodular functions allow to model many real-world optimisation problem...
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10/21/2020
Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem
In the area of evolutionary computation the calculation of diverse sets ...
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07/07/2020
Benchmarking in Optimization: Best Practice and Open Issues
This survey compiles ideas and recommendations from more than a dozen re...
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06/29/2020
Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem
In this work we focus on the well-known Euclidean Traveling Salesperson ...
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06/05/2020
Optimising Tours for the Weighted Traveling Salesperson Problem and the Traveling Thief Problem: A Structural Comparison of Solutions
The Traveling Salesperson Problem (TSP) is one of the best-known combina...
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05/28/2020
Dynamic Bi-Objective Routing of Multiple Vehicles
In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Pro...
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05/28/2020
Towards Decision Support in Dynamic Bi-Objective Vehicle Routing
We consider a dynamic bi-objective vehicle routing problem, where a subs...
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05/28/2020
More Effective Randomized Search Heuristics for Graph Coloring Through Dynamic Optimization
Dynamic optimization problems have gained significant attention in evolu...
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05/27/2020
Anytime Behavior of Inexact TSP Solvers and Perspectives for Automated Algorithm Selection
The Traveling-Salesperson-Problem (TSP) is arguably one of the best-know...
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04/22/2020
Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem
Evolutionary algorithms (EAs) are general-purpose problem solvers that u...
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04/20/2020
Evolving Diverse Sets of Tours for the Travelling Salesperson Problem
Evolving diverse sets of high quality solutions has gained increasing in...
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03/30/2020
Initial Design Strategies and their Effects on Sequential Model-Based Optimization
Sequential model-based optimization (SMBO) approaches are algorithms for...
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02/04/2020
The Node Weight Dependent Traveling Salesperson Problem: Approximation Algorithms and Randomized Search Heuristics
Several important optimization problems in the area of vehicle routing c...
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12/19/2019
One-Shot Decision-Making with and without Surrogates
One-shot decision making is required in situations in which we can evalu...
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03/09/2017
mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions
We present mlrMBO, a flexible and comprehensive R toolbox for model-base...
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01/05/2017