Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: A state-of-the-art
In recent years, there has been a growing research interest in integrating machine learning
techniques into meta-heuristics for solving combinatorial optimization problems. This …
techniques into meta-heuristics for solving combinatorial optimization problems. This …
An intensive and comprehensive overview of JAYA algorithm, its versions and applications
In this review paper, JAYA algorithm, which is a recent population-based algorithm is
intensively overviewed. The JAYA algorithm combines the survival of the fittest principle from …
intensively overviewed. The JAYA algorithm combines the survival of the fittest principle from …
A taxonomic review of metaheuristic algorithms for solving the vehicle routing problem and its variants
Recently, a taxonomic review of the Vehicle Routing Problem (VRP) literature published
between 2009 and June 2015 stated that most of the surveyed articles use metaheuristics …
between 2009 and June 2015 stated that most of the surveyed articles use metaheuristics …
Coronavirus herd immunity optimizer (CHIO)
In this paper, a new nature-inspired human-based optimization algorithm is proposed which
is called coronavirus herd immunity optimizer (CHIO). The inspiration of CHIO is originated …
is called coronavirus herd immunity optimizer (CHIO). The inspiration of CHIO is originated …
Boosted kernel search: Framework, analysis and case studies on the economic emission dispatch problem
R Dong, H Chen, AA Heidari, H Turabieh… - Knowledge-Based …, 2021 - Elsevier
In recent years, a variety of meta-heuristic nature-inspired algorithms have been proposed to
solve complex optimization problems. However, these algorithms suffer from the …
solve complex optimization problems. However, these algorithms suffer from the …
An improved gorilla troops optimizer for global optimization problems and feature selection
Abstract The Artificial Gorilla Groups Optimizer (GTO) is a novel metaheuristic algorithm that
takes its cues from the collective intelligence of wild gorilla troops. Although it has shown …
takes its cues from the collective intelligence of wild gorilla troops. Although it has shown …
A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems
IB Aydilek - Applied Soft Computing, 2018 - Elsevier
Optimization in computationally expensive numerical problems with limited function
evaluations provides computational advantages over constraints based on runtime …
evaluations provides computational advantages over constraints based on runtime …
Metaheuristic design of feedforward neural networks: A review of two decades of research
Over the past two decades, the feedforward neural network (FNN) optimization has been a
key interest among the researchers and practitioners of multiple disciplines. The FNN …
key interest among the researchers and practitioners of multiple disciplines. The FNN …
Symbiotic organisms search: a new metaheuristic optimization algorithm
This paper applies a new robust and powerful metaheuristic algorithm called Symbiotic
Organisms Search (SOS) to numerical optimization and engineering design problems. SOS …
Organisms Search (SOS) to numerical optimization and engineering design problems. SOS …
Search and rescue optimization algorithm: A new optimization method for solving constrained engineering optimization problems
A new optimization method namely the Search and Rescue optimization algorithm (SAR) is
presented here to solve constrained engineering optimization problems. This metaheuristic …
presented here to solve constrained engineering optimization problems. This metaheuristic …