response-surface-methodology

Python library for parallel multiobjective simulation optimization

Pareto Front Estimation Using Unit Hyperplane

Solver for Blackbox Multiobjective Optimization Problems

A/B/n Experiment Project using Response Surface Methodology

A few ML algorithms and Data Analysis

Response Surface Analysis Interactive Panel

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).

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

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.

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.

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

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

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.

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.

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