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[HTML][HTML] Simulation optimization applied to production scheduling in the era of industry 4.0: A review and future roadmap
Production Scheduling (PS) is an essential paradigm within supply and manufacturing
systems and an important element of sustainable development. PS, mainly known for its …
systems and an important element of sustainable development. PS, mainly known for its …
Cloud-load forecasting via decomposition-aided attention recurrent neural network tuned by modified particle swarm optimization
Recent improvements in networking technologies have led to a significant shift towards
distributed cloud-based services. However, adequate management of computation …
distributed cloud-based services. However, adequate management of computation …
Tuning attention based long-short term memory neural networks for Parkinson's disease detection using modified metaheuristics
Parkinson's disease (PD) is a progressively debilitating neurodegenerative disorder that
primarily affects the dopaminergic system in the basal ganglia, impacting millions of …
primarily affects the dopaminergic system in the basal ganglia, impacting millions of …
Designing new metaheuristics: manual versus automatic approaches
A metaheuristic is a collection of algorithmic concepts that can be used to define heuristic
methods applicable to a wide set of optimization problems for which exact/analytical …
methods applicable to a wide set of optimization problems for which exact/analytical …
Cloud computing load prediction by decomposition reinforced attention long short-term memory network optimized by modified particle swarm optimization algorithm
Computer resources provision over the internet resulted in the wide spread usage of cloud
computing paradigm. With the use of such resources come certain challenges that can …
computing paradigm. With the use of such resources come certain challenges that can …
Benchmarking in optimization: Best practice and open issues
This survey compiles ideas and recommendations from more than a dozen researchers with
different backgrounds and from different institutes around the world. Promoting best practice …
different backgrounds and from different institutes around the world. Promoting best practice …
A hybrid particle swarm optimizer with sine cosine acceleration coefficients
Particle swarm optimization (PSO) has been widely used to solve complex global
optimization tasks due to its implementation simplicity and inexpensive computational …
optimization tasks due to its implementation simplicity and inexpensive computational …
A novel stochastic fractal search algorithm with fitness-distance balance for global numerical optimization
Abstract Stochastic Fractal Search (SFS) is a new and original meta-heuristic search (MHS)
algorithm with strong foundations. As with many other MHS methods, there are problems in …
algorithm with strong foundations. As with many other MHS methods, there are problems in …
Optimization of type-2 fuzzy logic controller design using the GSO and FA algorithms
This paper presents a comparative study between the firefly algorithm (FA) and the galactic
swarm optimization (GSO) method, where the performance of both methods is observed and …
swarm optimization (GSO) method, where the performance of both methods is observed and …
Classifying Metaheuristics: Towards a unified multi-level classification system
Metaheuristics provide the means to approximately solve complex optimisation problems
when exact optimisers cannot be utilised. This led to an explosion in the number of novel …
when exact optimisers cannot be utilised. This led to an explosion in the number of novel …