Knapsack problems—An overview of recent advances. Part II: Multiple, multidimensional, and quadratic knapsack problems

V Cacchiani, M Iori, A Locatelli, S Martello - Computers & Operations …, 2022 - Elsevier
After the seminal books by Martello and Toth (1990) and Kellerer, Pferschy, and Pisinger
(2004), knapsack problems became a classical and rich research area in combinatorial …

Monitoring and identifying wind turbine generator bearing faults using deep belief network and EWMA control charts

H Li, J Deng, S Yuan, P Feng… - Frontiers in Energy …, 2021 - frontiersin.org
Wind turbines are widely installed as the new source of cleaner energy production. Dynamic
and random stress imposed on the generator bearing of a wind turbine may lead to …

Device association for RAN slicing based on hybrid federated deep reinforcement learning

YJ Liu, G Feng, Y Sun, S Qin… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Network slicing (NS) has been widely identified as a key architectural technology for 5G-and-
beyond systems by supporting divergent requirements in a sustainable way. In radio access …

River suspended sediment load prediction based on river discharge information: application of newly developed data mining models

SQ Salih, A Sharafati, K Khosravi, H Faris… - Hydrological …, 2020 - Taylor & Francis
Suspended sediment load (SSL) is one of the essential hydrological processes that affects
river engineering sustainability. Sediment has a major influence on the operation of dams …

Analyzing bearing faults in wind turbines: A data-mining approach

A Kusiak, A Verma - Renewable Energy, 2012 - Elsevier
Bearings are an essential part of turbine generators and gearboxes. Dynamic and
unpredictable stress causes the bearings to wear prematurely, leading to increased turbine …

A data-mining approach to monitoring wind turbines

A Kusiak, A Verma - IEEE Transactions on Sustainable Energy, 2011 - ieeexplore.ieee.org
The rapid expansion of wind farms has generated interest in operations and maintenance.
An operating wind turbine undergoes various state changes, including transformation from a …

[PDF][PDF] Refugee resettlement

D Delacrétaz, SD Kominers, A Teytelboym - University of Oxford …, 2016 - t8el.com
Over 100,000 refugees are permanently resettled from refugee camps to hosting countries
every year. Nevertheless, refugee resettlement processes in most countries are ad hoc …

A data-centric machine learning methodology: Application on predictive maintenance of wind turbines

M Garan, K Tidriri, I Kovalenko - Energies, 2022 - mdpi.com
Nowadays, the energy sector is experiencing a profound transition. Among all renewable
energy sources, wind energy is the most developed technology across the world. To ensure …

[HTML][HTML] Multi-objective sustainable location-districting for the collection of municipal solid waste: Two case studies

SM Darmian, S Moazzeni, LM Hvattum - Computers & Industrial …, 2020 - Elsevier
This paper presents a multi-objective location-districting optimization model for sustainable
collection of municipal solid waste, motivated by strategic waste management decisions in …

Optimal selective maintenance decisions for large serial k-out-of-n: G systems under imperfect maintenance

C Diallo, U Venkatadri, A Khatab, Z Liu - Reliability Engineering & System …, 2018 - Elsevier
The selective maintenance problem (SMP) arises in many large multicomponent systems
which are operated for consecutive missions interspersed with finite breaks during which …