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pymoo

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This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and multivariate) and use (1) Bayesian framework, (2) Pyomo package, (3) Genetic algorithm with local search, and (4) Pymoo package to find optimum design parameters and minimum energy consumption.

  • Updated Mar 15, 2023
  • Jupyter Notebook

Ship Routing Algorithms for Just-In-Time and Energy Efficient Voyages. By using a genetic algorithm we strive the lowest possible fuel consumption while at the same time keeping the scheduled deadlines. Two different specifications of the algorithm are available, one with a constant engine power, one with an over the route changeable engine power.

  • Updated Apr 8, 2023
  • Jupyter Notebook

This repository is an implementation of https://link.springer.com/chapter/10.1007/978-3-030-72699-7_35 article. it uses evolutionary strategy (NSGA-II algorithm specificially) to configure image filters parameters in order to attack adversarially to a neural network.

  • Updated Feb 11, 2023
  • Jupyter Notebook

This project implements a multi-objective optimization model using evolutionary algorithms to schedule maintenance of power generation units over multiple time intervals. The goal is to maximize system reserve margins while minimizing total maintenance costs, subject to operational and budgetary constraints.

  • Updated Jun 29, 2025
  • Python

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