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Found 5 papers, 1 papers with code
Optimal Design of Electric Machine with Efficient Handling of Constraints and Surrogate Assistance
Electric machine design optimization is a computationally expensive multi-objective optimization problem.
pysamoo: Surrogate-Assisted Multi-Objective Optimization in Python
Significant effort has been made to solve computationally expensive optimization problems in the past two decades, and various optimization methods incorporating surrogates into optimization have been proposed.
GPSAF: A Generalized Probabilistic Surrogate-Assisted Framework for Constrained Single- and Multi-objective Optimization
A study of multiple well-known population-based optimization algorithms is conducted with and without the proposed surrogate assistance on single- and multi-objective optimization problems with a maximum solution evaluation budget of 300 or less.
A Non-Dominated Sorting Based Customized Random-Key Genetic Algorithm for the Bi-Objective Traveling Thief Problem
In this paper, we propose a method to solve a bi-objective variant of the well-studied Traveling Thief Problem (TTP).
pymoo: Multi-objective Optimization in Python
To address this issue, we have developed pymoo, a multi-objective optimization framework in Python.
