{
  "id": "methodology:evolutionary",
  "_kind": "Methodology",
  "_file": "domain/methodologies/methodologies.yaml",
  "_cluster": "domain",
  "attributes": {
    "displayName": "Evolutionary Algorithm",
    "description": "Applies genetic/evolutionary algorithms to solution search. Initializes a\npopulation of candidate solutions, evaluates fitness of each, selects fittest\ncandidates as parents, creates offspring through crossover (combining parent\ntraits), applies random mutations to introduce variation, replaces least fit\nwith offspring, and repeats until convergence or maximum generations. Suited\nfor exploring large solution spaces with multiple competing approaches.\n",
    "methodologyKind": "research",
    "origin": "Classic evolutionary computing"
  },
  "outgoingEdges": [
    {
      "from": "methodology:evolutionary",
      "to": "domain:software-engineering",
      "kind": "applies_to"
    }
  ],
  "incomingEdges": [
    {
      "from": "lib-process:shared--evolutionary",
      "to": "methodology:evolutionary",
      "kind": "follows_methodology",
      "attributes": {
        "weight": 1
      }
    }
  ]
}