response-surface-methodology

Python library for parallel multiobjective simulation optimization

Pareto Front Estimation Using Unit Hyperplane

Solver for Blackbox Multiobjective Optimization Problems

Response Surface Analysis Interactive Panel

A few ML algorithms and Data Analysis

The project focuses on the analysis of experimental data regarding the continuous biomass production of a cyanobacterium of the genus Nostoc. The primary objective is to understand how different cultivation factors influence biological growth over time, monitored through optical density (OD).

A/B/n Experiment Project using Response Surface Methodology

ML surface-roughness (Ra) prediction for CFRP milling — TUSAŞ Lift Up graduation project (MACHINOVA): RSM regression, desktop app & REST API.

Rust library for statistical Design of Experiments — factorial/RSM/Taguchi designs, ANOVA, power analysis, multi-response optimization. Also available as a WebAssembly/npm package.

Compound-agnostic Design of Experiments (DOE) & Response Surface Methodology toolkit in Python. Config-driven factor/response setup with covariate (ANCOVA) and blocking support, Box-Behnken/CCD/factorial designs, ANOVA, desirability optimization, robust operating windows, publication-ready figures, and automated PDF reports. CLI + library

Sequential design-of-experiments and response-surface optimization study in R.

A Dynamic Pricing framework integrating Monte Carlo simulations for demand uncertainty analysis and Response Surface Methodology (RSM) to optimize pricing strategies and maximize revenue.

Validation harness and curated case datasets for the FORMULA-Sigma pharmaceutical formulation platform. Reproducibility package for the methods paper (harness: MIT; datasets: CC-BY-4.0). Platform engine is proprietary.

An agentic Design-of-Experiments and analysis assistant: plans experiments, runs sandboxed analysis code, fits response-surface models, and recommends the next run via Bayesian optimization.

Two-phase evaluation framework for the OpenAI Realtime API: VAD parameter optimisation via CCD/RSM and LLM-as-a-Judge scoring of medical simulation transcripts.

DOE, RSM, regression, and multi-objective optimization of 3D printing parameters for lightweight and high-strength UAV parts

Lagrangian simulation of ascorbic acid retention during spray drying of Myrciaria dubia extract. Box-Behnken RSM, Monte Carlo uncertainty, glass transition analysis. UNSA Arequipa, Peru.

Multi-Objective Optimization of 3 output functions based on 5 input variables using epsilon-constraint method in Pyomo. [developed using ChatGPT July 20 Version]

Open-source Design of Experiments in your browser. Factorial designs, ANOVA, response surfaces, optimization, and a publication-ready PDF report — without the $1,995 license.