Work

Memetic Algorithm for Energy Optimization in Point-to-Point Robotized Operations

Year: 2025

Type: article

Abstract: This paper presents a memetic algorithm (MA) for energy cost estimation of a robot path. The developed algorithm uses a random recombination genetic algorithm (GA) as the basis for the first stage of the algorithm and performs a local search based on feature importances determined from the data in the second stage. To allow for the faster determination of the solution quality, the algorithm uses an ML-driven fitness function, based on MLP, for the determination of path energy. The performed tests show that not only does the GA itself optimize the point-to-point paths well, but the usage of MA can lower the energy use by 58% on average (N = 100) when compared to a linear path between the same two points.

Source: Machines

DOI: 10.3390/machines14010035

Authors: Sandi Baressi Šegota, Domagoj Frank, Ivan Lorencin, Nikola Anđelić

Institutions: Juraj Dobrila University of Pula, University North, University of Rijeka

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funders: Sveučilište u Rijeci, LOEWE Zentrum AdRIA