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Combustion machine learning: Principles, progress and prospects
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
[HTML][HTML] Differential evolution: A recent review based on state-of-the-art works
Differential evolution (DE) is a popular evolutionary algorithm inspired by Darwin's theory of
evolution and has been studied extensively to solve different areas of optimisation and …
evolution and has been studied extensively to solve different areas of optimisation and …
Newton-Raphson-based optimizer: A new population-based metaheuristic algorithm for continuous optimization problems
Abstract The Newton-Raphson-Based Optimizer (NRBO), a new metaheuristic algorithm, is
suggested and developed in this paper. The NRBO is inspired by Newton-Raphson's …
suggested and developed in this paper. The NRBO is inspired by Newton-Raphson's …
Dwarf mongoose optimization algorithm
This paper proposes a new metaheuristic algorithm called dwarf mongoose optimization
algorithm (DMO) to solve the classical and CEC 2020 benchmark functions and 12 …
algorithm (DMO) to solve the classical and CEC 2020 benchmark functions and 12 …
RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method
The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers.
Most of these cliché methods mimic animals' searching trends and possess a small …
Most of these cliché methods mimic animals' searching trends and possess a small …
[HTML][HTML] Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms
Metaheuristics are popularly used in various fields, and they have attracted much attention
in the scientific and industrial communities. In recent years, the number of new metaheuristic …
in the scientific and industrial communities. In recent years, the number of new metaheuristic …
Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts
Y Yang, H Chen, AA Heidari, AH Gandomi - Expert Systems with …, 2021 - Elsevier
A recent set of overused population-based methods have been published in recent years.
Despite their popularity, most of them have uncertain, immature performance, partially done …
Despite their popularity, most of them have uncertain, immature performance, partially done …
Human evolutionary optimization algorithm
J Lian, G Hui - Expert Systems with Applications, 2024 - Elsevier
This paper introduces the Human Evolutionary Optimization Algorithm (HEOA), a
metaheuristic algorithm inspired by human evolution. HEOA divides the global search …
metaheuristic algorithm inspired by human evolution. HEOA divides the global search …
Quadratic interpolation and a new local search approach to improve particle swarm optimization: Solar photovoltaic parameter estimation
Abstract The Particle Swarm Optimization technique (PSO) is widely used in practical
applications due to its flexibility and strong optimization performance. However, like other …
applications due to its flexibility and strong optimization performance. However, like other …
A reinforcement learning based RMOEA/D for bi-objective fuzzy flexible job shop scheduling
The flexible job shop scheduling problem (FJSP) is significant for realistic manufacturing.
However, the job processing time usually is uncertain and changeable during …
However, the job processing time usually is uncertain and changeable during …