Optienv: Introduction

Optienv is a lightweight, simulator‑friendly framework for multi‑objective optimization (MOO). It wraps external models with a simple CSV interface and runs evolutionary algorithms—currently NSGA‑II and NSGA‑III—at scale.

Design goals

  • Reproducible experiments Single-file per‑seed histories, optional checkpoints/resume, and fixed seeds.

  • Simulator integration CSV adapter reads decision vectors and writes objectives—no refactoring in your model.

  • Many‑objective capability NSGA‑III with reference directions for high‑dimensional objectives (≥ 4).

  • Actionable analysis Global Pareto front extraction and normalized hypervolume (HV) computation, including density control via --epsilon.

Key features

  • Two algorithms - NSGA‑II (dominance ranking + crowding distance) - NSGA‑III (dominance ranking + reference‑direction niching)

  • CSV model adapter - Writes variable_values.csv for your wrapper - Expects objective_values.csv back from the wrapper - Converts maximize objectives to minimization internally

  • Results management - One history CSV per seed: results/history_seed{SEED}.csv - Optional final CSVs: population, fitness, non‑dominated (nd) mask

  • Analysis - front: global non‑dominated set (optionally thinned by ε‑boxes) - hypervolume: normalized HV per generation (wide format)