Estimation of distribution algorithms using Gaussian Bayesian networks to solve industrial optimization problems constrained by environment variables

DOI10.1007/s10878-022-00879-6zbMath1497.90200OpenAlexW4283746863WikidataQ114225856 ScholiaQ114225856MaRDI QIDQ2165268

Concha Bielza, Pedro Larrañaga, Vicente P. Soloviev

Publication date: 19 August 2022

Published in: Journal of Combinatorial Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10878-022-00879-6

zbMATH Keywords

optimizationevolutionary algorithmsGaussian Bayesian networkestimation of distribution algorithmsindustryenvironment variables

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Sensitivity, stability, parametric optimization (90C31)

Cites Work

• Solving efficiently the 0-1 multi-objective knapsack problem
• An estimation of distribution algorithm for public transport driver scheduling
• The n-Queens Problem
• Algorithm 989
• Bayesian Graphical Models for Discrete Data
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Estimation of distribution algorithms using Gaussian Bayesian networks to solve industrial optimization problems constrained by environment variables