II.
LibrarySkill overview
Reference · livelib-skill:mathematics--derivative-free-optimization
derivative-free-optimization overview
Optimization without gradient information
Attributes
displayName
derivative-free-optimization
description
Optimization without gradient information
libraryPath
library/specializations/domains/science/mathematics/skills/derivative-free-optimization/SKILL.md
specialization
mathematics
contentSummary
# Derivative-Free Optimization
## Purpose
Provides optimization capabilities for problems where gradient information is unavailable or unreliable.
## Capabilities
- Nelder-Mead simplex method
- Powell's method
- Surrogate-based optimization
- Bayesian optimization
- Pattern search me
Outgoing edges
lib_applies_to_domain1
- domain:mathematics·DomainMathematics
lib_belongs_to_specialization2
- specialization:computational-mathematics·SpecializationComputational Mathematics
- specialization:mathematics·SpecializationMathematics
lib_implements_workflow1
- workflow:experiment-design·WorkflowExperiment Design
lib_involves_role2
- role:computational-scientist·RoleComputational Scientist
- role:research-engineer·RoleResearch Engineer
lib_requires_skill_area3
- skill-area:np-hard-heuristics·SkillAreaHeuristics for NP-Hard Problems
- skill-area:mathematical-reasoning·SkillAreaMathematical Reasoning
- skill-area:dynamic-programming·SkillAreaDynamic Programming
Incoming edges
None.