Optimization Methods
CommunityMaster optimization with metaheuristics.
Design & Creative#optimization#multi-objective#genetic-algorithm#particle-swarm#simulated-annealing#aec
Authorgerald-ica
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Optimizing complex design problems in AEC by applying a comprehensive toolkit of optimization algorithms, enabling rigorous trade-offs and automated exploration instead of manual tuning.
Core Features & Use Cases
- Broad algorithm coverage: genetic algorithms, simulated annealing, PSO, gradient-based methods, topology optimization, and surrogate/metaheuristic techniques.
- Multi-objective design: explore weight, cost, energy, carbon, and performance trade-offs with Pareto-front visualization.
- Real-world workflows: apply automated optimization to architectural sizing, layout, and form-finding; identify robust solutions under constraints.
Quick Start
Generate a multi-algorithm plan for an architectural design problem using GA, SA, and PSO to explore trade-offs.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Optimization Methods Download link: https://github.com/gerald-ica/opencode-config-snapshot/archive/main.zip#optimization-methods Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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