A tutorial on the design, experimentation and application of metaheuristic algorithms to real-world optimization problems

E Osaba, E Villar-Rodriguez, J Del Ser… - Swarm and Evolutionary …, 2021 - Elsevier
In the last few years, the formulation of real-world optimization problems and their efficient
solution via metaheuristic algorithms has been a catalyst for a myriad of research studies. In …

[HTML][HTML] The role of simulation and serious games in teaching concepts on circular economy and sustainable energy

R De la Torre, BS Onggo, CG Corlu, M Nogal, AA Juan - Energies, 2021 - mdpi.com
The prevailing need for a more sustainable management of natural resources depends not
only on the decisions made by governments and the will of the population, but also on the …

Walrus optimizer: A novel nature-inspired metaheuristic algorithm

M Han, Z Du, KF Yuen, H Zhu, Y Li, Q Yuan - Expert Systems with …, 2024 - Elsevier
Metaheuristic algorithms are intelligent optimization approaches that lead the searching
procedure through utilizing exploitation and exploration. The increasing complexity of real …

Improving construction and demolition waste collection service in an urban area using a simheuristic approach: A case study in Sydney, Australia

M Yazdani, K Kabirifar, BE Frimpong, M Shariati… - Journal of Cleaner …, 2021 - Elsevier
Urbanization and population growth have resulted in a significant increase in the amount of
generated construction and demolition (C&D) waste worldwide. Improper C&D waste …

[HTML][HTML] Multi-agent deep reinforcement learning based Predictive Maintenance on parallel machines

MLR Rodríguez, S Kubler, A de Giorgio… - Robotics and Computer …, 2022 - Elsevier
In the context of Industry 4.0, companies understand the advantages of performing
Predictive Maintenance (PdM). However, when moving towards PdM, several …

Optimization challenges in vehicle-to-grid (V2G) systems and artificial intelligence solving methods

M Escoto, A Guerrero, E Ghorbani, AA Juan - Applied Sciences, 2024 - mdpi.com
Vehicle-to-grid (V2G) systems play a key role in the integration of electric vehicles (EVs) into
smart grids by enabling bidirectional energy flows between EVs and the grid. Optimizing …

A review of the role of heuristics in stochastic optimisation: From metaheuristics to learnheuristics

AA Juan, P Keenan, R Martí, S McGarraghy… - Annals of Operations …, 2023 - Springer
In the context of simulation-based optimisation, this paper reviews recent work related to the
role of metaheuristics, matheuristics (combinations of exact optimisation methods with …

[HTML][HTML] Edge computing and iot analytics for agile optimization in intelligent transportation systems

M Peyman, PJ Copado, RD Tordecilla, LC Martins… - Energies, 2021 - mdpi.com
With the emergence of fog and edge computing, new possibilities arise regarding the data-
driven management of citizens' mobility in smart cities. Internet of Things (IoT) analytics …

Bioinspired algorithms for multiple sequence alignment: a systematic review and roadmap

MK Ibrahim, UK Yusof, TAE Eisa, M Nasser - Applied Sciences, 2024 - mdpi.com
Multiple Sequence Alignment (MSA) plays a pivotal role in bioinformatics, facilitating various
critical biological analyses, including the prediction of unknown protein structures and …

Metaheuristic optimization algorithms: An overview

B Brahim, M Kobayashi, M Al Ali… - HCMCOU …, 2024 - journalofscience.acs.ou.edu.vn
Metaheuristic optimization algorithms are known for their versatility and adaptability, making
them effective tools for solving a wide range of complex optimization problems. They don't …