8 citations · 11 across the 2 of their papers we have counts for
4 papers
pysamoo: Surrogate-Assisted Multi-Objective Optimization in Python
Julian Blank, Kalyanmoy Deb
Significant effort has been made to solve computationally expensive optimization problems in the past two decades, and various optimization methods incorporating surrogates into op…
GPSAF: A Generalized Probabilistic Surrogate-Assisted Framework for Constrained Single- and Multi-objective Optimization
Julian Blank, Kalyanmoy Deb
Significant effort has been made to solve computationally expensive optimization problems in the past two decades, and various optimization methods incorporating surrogates into op…
A Non-Dominated Sorting Based Customized Random-Key Genetic Algorithm for the Bi-Objective Traveling Thief Problem
Jonatas B. C. Chagas, Julian Blank, Markus Wagner +2
In this paper, we propose a method to solve a bi-objective variant of the well-studied Traveling Thief Problem (TTP). The TTP is a multi-component problem that combines two classic…
pymoo: Multi-objective Optimization in Python
Julian Blank, Kalyanmoy Deb
Python has become the programming language of choice for research and industry projects related to data science, machine learning, and deep learning. Since optimization is an inher…