406 citations · 538 across the 10 of their papers we have counts for
11 papers
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games
Vanessa Volz, Boris Naujoks, Pascal Kerschke +1
The term Procedural Content Generation (PCG) refers to the (semi-)automatic generation of game content by algorithmic means, and its methods are becoming increasingly popular in ga…
Characterization of Constrained Continuous Multiobjective Optimization Problems: A Performance Space Perspective
Aljoša Vodopija, Tea Tušar, Bogdan Filipič
Constrained multiobjective optimization has gained much interest in the past few years. However, constrained multiobjective optimization problems (CMOPs) are still unsatisfactorily…
Characterization of Constrained Continuous Multiobjective Optimization Problems: A Feature Space Perspective
Aljoša Vodopija, Tea Tušar, Bogdan Filipič
Despite the increasing interest in constrained multiobjective optimization in recent years, constrained multiobjective optimization problems (CMOPs) are still unsatisfactory unders…
Identifying Properties of Real-World Optimisation Problems through a Questionnaire
Koen van der Blom, Timo M. Deist, Vanessa Volz +5
Optimisation algorithms are commonly compared on benchmarks to get insight into performance differences. However, it is not clear how closely benchmarks match the properties of rea…
Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems
Koen van der Blom, Timo M. Deist, Tea Tušar +5
Benchmarks are a useful tool for empirical performance comparisons. However, one of the main shortcomings of existing benchmarks is that it remains largely unclear how they relate…
COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite
Ouassim Elhara, Konstantinos Varelas, Duc Nguyen +4
The bbob-largescale test suite, containing 24 single-objective functions in continuous domain, extends the well-known single-objective noiseless bbob test suite, which has been use…
COCO: Performance Assessment
Nikolaus Hansen, Anne Auger, Dimo Brockhoff +2
We present an any-time performance assessment for benchmarking numerical optimization algorithms in a black-box scenario, applied within the COCO benchmarking platform. The perform…
Biobjective Performance Assessment with the COCO Platform
Dimo Brockhoff, Tea Tušar, Dejan Tušar +3
This document details the rationales behind assessing the performance of numerical black-box optimizers on multi-objective problems within the COCO platform and in particular on th…
Using Well-Understood Single-Objective Functions in Multiobjective Black-Box Optimization Test Suites
Dimo Brockhoff, Tea Tusar, Anne Auger +1
Several test function suites are being used for numerical benchmarking of multiobjective optimization algorithms. While they have some desirable properties, like well-understood Pa…
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
Nikolaus Hansen, Anne Auger, Raymond Ros +3
We introduce COCO, an open source platform for Comparing Continuous Optimizers in a black-box setting. COCO aims at automatizing the tedious and repetitive task of benchmarking num…
COCO: The Experimental Procedure
Nikolaus Hansen, Tea Tusar, Olaf Mersmann +2
We present a budget-free experimental setup and procedure for benchmarking numericaloptimization algorithms in a black-box scenario. This procedure can be applied with the COCO ben…