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A tutorial on the design, experimentation and application of metaheuristic algorithms to real-world optimization problems
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 …
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
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 …
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 …
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
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 …
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
In the context of Industry 4.0, companies understand the advantages of performing
Predictive Maintenance (PdM). However, when moving towards PdM, several …
Predictive Maintenance (PdM). However, when moving towards PdM, several …
Optimization challenges in vehicle-to-grid (V2G) systems and artificial intelligence solving methods
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 …
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
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 …
role of metaheuristics, matheuristics (combinations of exact optimisation methods with …
[HTML][HTML] Edge computing and iot analytics for agile optimization in intelligent transportation systems
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 …
driven management of citizens' mobility in smart cities. Internet of Things (IoT) analytics …
Bioinspired algorithms for multiple sequence alignment: a systematic review and roadmap
Multiple Sequence Alignment (MSA) plays a pivotal role in bioinformatics, facilitating various
critical biological analyses, including the prediction of unknown protein structures and …
critical biological analyses, including the prediction of unknown protein structures and …
Metaheuristic optimization algorithms: An overview
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 …
them effective tools for solving a wide range of complex optimization problems. They don't …