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problems.yaml
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3597 lines (3597 loc) · 72.5 KB
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fn_ato:
allows_partial_evaluation: no
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: 'Parameters of the Modules of the Automatic Train Operation are optimized;
two objectives: minimizing energy consumption and minimizing driving duration.'
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations: null
instances: null
long_name: null
modality:
- unimodal
name: ATO
noise_type: null
objectives:
- 2
references: null
source:
- real-world
tags: null
type: problem
variables:
- dim: 10
type: continuous
fn_building_spatial:
allows_partial_evaluation: no
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: yes
number: null
type: box
- equality: null
hard: yes
number: null
type: unknown
description: Optimise the spatial layout of a building to minimise energy
consumption for climate control and minimise the strain on the structure.
Many hard constraints; mixed-variable (continuous+binary); expensive
evaluations.
dynamic_type: null
evaluation_time:
- 40 seconds
- 1 second
fidelity_levels: null
implementations:
- impl_bso_toolbox
instances: null
long_name: null
modality: null
name: Building spatial design
noise_type: null
objectives:
- 2
references:
- authors: []
link:
type: null
url: https://hdl.handle.net/1887/81789
title: Building spatial design
source:
- real-world
tags: null
type: problem
variables:
- dim:
max: null
min: 1
type: continuous
- dim:
max: null
min: 1
type: binary
fn_convex_dtlz2:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: Variant of DTLZ2 with a convex Pareto front (instead of concave)
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations: null
instances: null
long_name: null
modality: null
name: Convex DTLZ2
noise_type: null
objectives:
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
references:
- authors: []
link:
type: null
url: https://doi.org/10.1109/TEVC.2013.2281535
title: Convex DTLZ2
source: null
tags: null
type: problem
variables:
- dim:
max: null
min: 1
type: continuous
fn_emdo:
allows_partial_evaluation: no
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: yes
number: null
type: box
- equality: null
hard: some
number: null
type: unknown
- equality: null
hard: yes
number: 12
type: unknown
description: "# Goal\nFind a design of a synchronous electric motor for power steering
systems that minimizes costs and satisfies all constraints.\n\n# Motivation\n\
Challenging to find good solutions in a limited time.\n\n# Key Challenges\n* Time-consuming
solution evaluation\n* Highly-constrained problem\n* Constraints are multimodal\n\
\nThis is not an available problem, but could be interesting to show to researchers
which difficulties appear in real-world problems."
dynamic_type: null
evaluation_time:
- 8 minutes
fidelity_levels: null
implementations:
- impl_emdo
instances: null
long_name: Electric Motor Design Optimization
modality:
- multimodal
name: Electric Motor Design Optimization
noise_type:
- noisy
objectives:
- 1
references:
- authors:
- Tea Tušar
- Peter Korošec
- Bogdan Filipič
link:
type: null
url: https://dis.ijs.si/tea/Publications/Tusar23Multistep.pdf
title: A Multi-Step Evaluation Process in Electric Motor Design
source:
- real-world
tags: null
type: problem
variables:
- dim: 13
type: continuous
- dim: 13
type: integer
fn_fleetopt:
allows_partial_evaluation: yes
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: yes
number: null
type: unknown
description: 'UK healthcare organisation fleet optimisation: reduce the fleet of
non-emergency healthcare trip vehicles while still ensuring all trips can be covered.
Bilevel: upper level 54 vars, lower level 13208 vars.'
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations: null
instances: null
long_name: null
modality: null
name: FleetOpt
noise_type: null
objectives:
- 1
references:
- authors: []
link:
type: null
url: https://dl.acm.org/doi/abs/10.1145/3638530.3664137
title: FleetOpt
source:
- real-world
tags: null
type: problem
variables:
- dim:
- 13208
- 54
type: integer
fn_gasoline:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: yes
number: 5
type: unknown
description: Multi-objective optimization to minimize fuel consumption and NOx
emissions over a two-minute dynamic duty cycle, subject to five constraints
(turbine inlet temperature, knock occurrences, peak cylinder pressure, peak
cylinder pressure rise, total work). Seven decision variables cover hardware
choices and engine control parameters.
dynamic_type: null
evaluation_time: []
fidelity_levels:
- 1
- 2
implementations:
- impl_gasoline
instances: null
long_name: null
modality: null
name: Gasoline direct injection engine design
noise_type: null
objectives:
- 2
references:
- authors: []
link:
type: null
url: https://doi.org/10.1016/j.ejor.2022.08.032
title: Gasoline direct injection engine design
source:
- real-world
tags: null
type: problem
variables:
- dim: 7
type: continuous
- dim: 7
type: integer
fn_invdeceptive_deceptive_rotell:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: null
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations: null
instances: null
long_name: null
modality: null
name: InverseDeceptiveTrap+RotatedEllipsoid / DeceptiveTrap+RotatedEllipsoid
noise_type: null
objectives:
- 2
references:
- authors: []
link:
type: null
url: https://doi.org/10.1145/3449726.3459521
title: Mixed-variable multi-objective test problems
source:
- artificial
tags: null
type: problem
variables:
- dim:
max: null
min: 1
type: continuous
- dim:
max: null
min: 1
type: binary
fn_inverted_dtlz1:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: Variant of DTLZ1 with an inverted Pareto front
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations: null
instances: null
long_name: null
modality: null
name: Inverted DTLZ1
noise_type: null
objectives:
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
references:
- authors: []
link:
type: null
url: https://doi.org/10.1109/TEVC.2013.2281534
title: Inverted DTLZ1
source: null
tags: null
type: problem
variables:
- dim:
max: null
min: 1
type: continuous
fn_jsec2019:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: yes
number: 22
type: unknown
description: expensive evaluations 3s; 22 constraints
dynamic_type: null
evaluation_time:
- 3s
fidelity_levels: null
implementations:
- impl_jsec2019
instances: null
long_name: null
modality: null
name: JSEC2019
noise_type: null
objectives:
- 1
- 2
- 3
- 4
- 5
references:
- authors: []
link:
type: null
url:
http://www.jpnsec.org/files/competition2019/EC-Symposium-2019-Competition-English.html
title: JPNSEC EC-Symposium 2019 competition
source:
- real-world
tags: null
type: problem
variables:
- dim: 32
type: continuous
fn_onemax_sphere_deceptive_rotell:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: null
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations: null
instances: null
long_name: null
modality: null
name: Onemax+Sphere / DeceptiveTrap+RotatedEllipsoid
noise_type: null
objectives:
- 2
references:
- authors: []
link:
type: null
url: https://doi.org/10.1145/3449726.3459521
title: Mixed-variable multi-objective test problems
source:
- artificial
tags: null
type: problem
variables:
- dim:
max: null
min: 1
type: continuous
- dim:
max: null
min: 1
type: binary
fn_onemax_sphere_zeromax_sphere:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: null
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations: null
instances: null
long_name: null
modality: null
name: Onemax+Sphere / Zeromax+Sphere
noise_type: null
objectives:
- 2
references:
- authors: []
link:
type: null
url: https://doi.org/10.1145/3449726.3459521
title: Onemax+Sphere / Zeromax+Sphere
source:
- artificial
tags: null
type: problem
variables:
- dim:
max: null
min: 1
type: continuous
- dim:
max: null
min: 1
type: binary
fn_radar_waveform:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: yes
number: null
type: unknown
description: null
dynamic_type: null
evaluation_time: []
fidelity_levels: null
implementations:
- impl_radar_waveform
instances: null
long_name: null
modality: null
name: Radar waveform
noise_type: null
objectives:
- 9
references:
- authors: []
link:
type: null
url: https://doi.org/10.1007/978-3-540-70928-2_53
title: Radar waveform design
source:
- real-world
tags: null
type: problem
variables:
- dim:
max: 12
min: 4
type: integer
gen_beacon:
allows_partial_evaluation: no
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: yes
number: 0
type: box
description: Generator for bi-objective benchmark problems with explicitly
controlled correlations in continuous spaces. Multimodal with random
structure.
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_beacon
long_name: Continuous Bi-objective Benchmark problems with Explicit Adjustable
COrrelatioN control
modality:
- multimodal
name: BEACON
noise_type: null
objectives:
- 2
references:
- authors: []
link:
type: null
url: https://dl.acm.org/doi/10.1145/3712255.3734303
title: BEACON
source:
- artificial
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
gen_bono_bench:
allows_partial_evaluation: no
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: yes
number: null
type: box
description: Bi-objective problem generator and suite with scalable continuous
decision space. Features complex problem properties and Pareto front
approximations with error guarantees for the hypervolume and exact R2
indicators.
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_bonobench
long_name: Bi-objective Numerical Optimization Benchmark
modality:
- multimodal
name: BONO-Bench
noise_type: null
objectives:
- 2
references: null
source:
- artificial
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
gen_ealain:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: some
number: null
type: unknown
description: Real-world-like, easily extensible to increase complexity
dynamic_type:
- optional
evaluation_time: null
fidelity_levels:
- 1
- 2
implementations:
- impl_ealain
long_name: null
modality: null
name: Ealain
noise_type: null
objectives:
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
references:
- authors: []
link:
type: null
url: https://doi.org/10.1145/3638530.3654299
title: Ealain
source:
- real-world-like
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
- dim:
max: null
min: 1
type: binary
- dim:
max: null
min: 1
type: integer
gen_gnbg:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: Generator counterpart of GNBG.
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_gnbg
long_name: null
modality: null
name: GNBG
noise_type: null
objectives:
- 1
references:
- authors: []
link:
type: null
url: https://arxiv.org/abs/2312.07083
title: GNBG
source:
- artificial
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
gen_gnbg_ii:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: Generator counterpart of GNBG-II.
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_gnbg_ii
- impl_iohgnbg
long_name: null
modality: null
name: GNBG-II
noise_type: null
objectives:
- 1
references:
- authors: []
link:
type: null
url: https://dl.acm.org/doi/pdf/10.1145/3712255.3734271
title: GNBG-II
source:
- artificial
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
gen_gpd:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints:
- equality: null
hard: some
number: null
type: unknown
description: null
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations: null
long_name: null
modality: null
name: GPD
noise_type:
- optional
objectives:
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
references:
- authors: []
link:
type: null
url: https://doi.org/10.1016/j.asoc.2020.106139
title: GPD generator
source: null
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
gen_iohclustering:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: Generator counterpart of the IOHClustering suite.
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_iohclustering
long_name: null
modality:
- multimodal
name: IOHClustering
noise_type: null
objectives:
- 1
references:
- authors: []
link:
type: null
url: https://arxiv.org/pdf/2505.09233
title: IOHClustering
source:
- artificial-from-real-data
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
gen_ma_bbob:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: Generator that creates affine combinations of BBOB functions
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_iohexperimenter
- impl_ma_bbob
long_name: null
modality:
- multimodal
name: MA-BBOB
noise_type: null
objectives:
- 1
references:
- authors: []
link:
type: null
url: https://doi.org/10.1145/3673908
title: MA-BBOB
source:
- artificial
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
gen_mpm2:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: nonlinear nonseparable nonsymmetric; scalable in terms of time to
evaluate the objective function
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_mpm2
long_name: null
modality:
- multimodal
name: MPM2
noise_type: null
objectives:
- 1
references:
- authors: []
link:
type: null
url: https://ls11-www.cs.tu-dortmund.de/_media/techreports/tr15-01.pdf
title: MPM2 technical report TR15-01
source: null
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
gen_mubqp:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: tunable variable and objective dimensions; tunable density and
correlation between objectives
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_mocobench
long_name: null
modality:
- multimodal
- quadratic
name: mUBQP
noise_type: null
objectives:
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
references:
- authors: []
link:
type: null
url: https://doi.org/10.1016/j.asoc.2013.11.008
title: mUBQP benchmark
source: null
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: binary
gen_puboi:
allows_partial_evaluation: no
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: A benchmark in which variable importance is tunable, based on the
Walsh function.
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_puboi
long_name: Polynomial Unconstrained Binary Optimization with tunable
importance
modality: null
name: PUBOi
noise_type: null
objectives:
- 1
references:
- authors: []
link:
type: null
url: https://link.springer.com/chapter/10.1007/978-3-031-04148-8_12
title: PUBOi
source:
- artificial
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: binary
gen_randoptgen:
allows_partial_evaluation: no
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: A Unified Random Problem Generator for Single- and
Multi-Objective Optimization Problems with Mixed-Variable Input Spaces.
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_randoptgen
long_name: RandOptGen
modality:
- multimodal
name: RandOptGen
noise_type: null
objectives:
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
references: null
source:
- artificial
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: continuous
- dim:
max: null
min: 1
type: binary
- dim:
max: null
min: 1
type: integer
gen_rho_mnk_landscapes:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: tunable variable and objective dimensions; tunable multimodality
and correlation between objectives
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_mocobench
long_name: null
modality:
- multimodal
name: ρMNK-Landscapes
noise_type: null
objectives:
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
references:
- authors: []
link:
type: null
url: https://doi.org/10.1016/j.ejor.2012.12.019
title: On the design of multi-objective evolutionary algorithms based on
NK-landscapes
source: null
tags: null
type: generator
variables:
- dim:
max: null
min: 1
type: binary
gen_rho_mtsp:
allows_partial_evaluation: null
can_evaluate_objectives_independently: null
code_examples: null
constraints: null
description: tunable variable and objective dimensions; tunable instance type
(euclidean/random); tunable correlation between objectives
dynamic_type: null
evaluation_time: null
fidelity_levels: null
implementations:
- impl_mocobench
long_name: null
modality:
- multimodal
- quadratic
name: ρmTSP