metaheuristic-optimisation
There are 3 repositories under metaheuristic-optimisation topic.
kkg1999 / MetaheuristicOptimization
Different meta-heuristic optimization techniques for feature selection
atom-search-optimizationbarnacles-mating-optimizerequilibrium-optimizergenetic-algorithmgolden-ratio-optimizationmanta-ray-foraging-optimizationmetaheuristicmetaheuristic-algorithmsmetaheuristic-frameworkmetaheuristic-optimisationmetaheuristicsoptimizationoptimization-algorithmsparticle-swarm-optimizationsailfish-optimizersocial-mimic-optimizationLanguage:Python 37- Language:Jupyter Notebook 26
jigsaw373 / evolutionary
A list of optimization algorithms and their sample codes
Language:Python 26jcrvz / customhys
Customising optimisation metaheuristics via hyper-heuristic search (CUSTOMHyS). This framework provides tools for solving, but not limited to, continuous optimisation problems using a hyper-heuristic approach for customising metaheuristics. Such an approach is powered by a strategy based on Simulated Annealing. Also, several search operators serve as building blocks for tailoring metaheuristics. They were extracted from ten well-known metaheuristics in the literature.
Language:Python 17ali-ece / Design-of-optimal-CMOS-ring-oscillator-using-an-intelligent-optimization-tool
This paper presents an intelligent sizing method to improve the performance and efficiency of a CMOS Ring Oscillator (RO). The proposed approach is based on the simultaneous utilization of powerful and new multi-objective optimization techniques along with a circuit simulator under a data link. The proposed optimizing tool creates a perfect tradeoff between the contradictory objective functions in CMOS RO optimal design. This tool is applied for intelligent estimation of the circuit parameters (channel width of transistors), which have a decisive influence on RO specifications. Along the optimal RO design in an specified range of oscillaton frequency, the Power Consumption, Phase Noise, Figure of Merit (FoM), Integration Index, Design Cycle Time are considered as objective functions. Also, in generation of Pareto front some important issues, i.e. Overall Nondominated Vector Generation (ONVG), and Spacing (S) are considered for more effectiveness of the obtained feasible solutions in application. Four optimization algorithms called Multi-Objective Genetic Algorithm (MOGA), Multi-Objective Inclined Planes system Optimization (MOIPO), Multi-Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Modified Inclined Planes System Optimization (MOMIPO) are utilized for 0.18-mm CMOS technology with supply voltage of 1-V. Baesd on our extensive simulations and experimental results MOMIPO outperforms the best performance among other multi-objective algorithms in presented RO designing tool.
multi-objective-optimizationpareto-optimalitypareto-frontoptimizationoptimization-algorithmsswarm-intelligenceevolutionary-algorithmsevolutionary-computationengineering-optimisationbio-inspired-optimizationheuristic-search-algorithmsmetaheuristic-optimisationmetaheuristic-algorithmsvlsi-circuitshspicematlab- SOS
facaraff / SOS
The Stochastic Optimisation Software (SOS) is a research-oriented software platform for Metaheuristic Optimisation (Stochastic Optimisation). If you are using SOS, please acknowledge the article "Caraffini, F.; Iacca, G. The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms. Mathematics 2020, 8, 785." (https://doi.org/10.3390/math8050785)
Language:Java 9 angelinbeni / Remora_Optimization_Algorithm
Matlab code for Remora Optimization Algorithm (ROA)
Language:MATLAB 8- Language:Python 8
Muradmustafayev-03 / Optimisation-Algorithms
A collection of the most commonly used Optimisation Algorithms for Data Science & Machine Learning
Language:Python 8ToKiNoBug / HeuristicFlow
C++ template classes of metaheuristic algorithms including GA, NSGA2, NSGA3, PSO,AOS, etc
Language:C++ 7- Duelist-Algorithm-Python
tsyet12 / Duelist-Algorithm-Python
A Python implementation of the paper "Duelist Algorithm: An Algorithm Inspired by How Duelist Improve Their Capabilities in a Duel" https://arxiv.org/abs/1512.00708
genetic-algorithmgenetic-optimization-algorithmmulti-objective-optimizationevolutionary-algorithmsevolutionary-algorithmevolutionary-computationmetaheuristicsmetaheuristics-frameworkmetaheuristic-optimisationduelist-algorithmartificial-intelligence-algorithmsartificial-intelligencepython3pythoncomputational-intelligenceoptimizationoptimization-algorithmsoptimization-toolsoptimization-methodsoptimization-algorithm-libraryLanguage:Python 7 A new optimization method based on the dynamic of sliding motion along a frictionless inclined plane. In IPO, a collection of agents cooperate with each other and move toward better positions in the search space by employing Newton’s second law and equations of motion. The standard version of the IPO is presented by Mozafari et al. in 2016. Powerful improved versions of it called MIPO and SIPO along with its multi-objective version of MOIPO were presented in 2016, 2017 and 2019 by Dr. Ali Mohammadi (myself) and colleagues at the University of Birjand, respectively. This powerful algorithm has also been used in many applications, which has provided very good outputs. In the following, the standard version of the IPO algorithm along with the benchmark functions reviewed in its reference article, and its improved versions are attached.
Language:MATLAB 5bghojogh / Metaheuristic-Optimization
The codes for metaheuristic optimization algorithms
Language:Python 5jonasgrebe / bees-bats-fireflies
Implementation of three nature-inspired search algorithms: Bees Algorithm, Bat Algorithm, and Firefly Algorithm
Language:HTML 5Python code for African vulture optimization algorithm
Language:Jupyter Notebook 4edoardo262632 / DBDS-optimization
University assignment project for the Optimization Methods and Algorithms at PoliTO
Language:C++ 4FelipeRamosOliveira / Portfolio
The purpose of this repository is to present applications of different programming languages in scientific problems.
Language:Jupyter Notebook 4- Language:MATLAB 4
- tcc-salbp2
joao-vitor-costa / tcc-salbp2
Simple Assembly Line Balancing Problem Type 2
Language:C++ 4 mike-gimelfarb / cocoa
Large suite of algorithms for black-box optimization in C++ with python wrappers.
Language:C++ 4mrsebai / DSTI-coursework
All courses assignements, exams and projects done during the year study at Data ScienceTech Institute (DSTI).
Language:C 4NisanurBulut / TezRota
Routing problem in heterogeneous fleet is discussed.
Language:C# 4The code for Pontogammarus Maeoticus Swarm Optimization (PMSO) which is a metaheuristic optimization algorithm
Language:MATLAB 3ErkanCetinyamac / Vehicle-Routing-Problem-An-Optimization-Solution-with-Tabu-Search-Algorithm
An optimization solution with tabu search to VRP Problem.
Language:Jupyter Notebook 3- Language:MATLAB 3
xjcheam / portfolio-optimization-qts-trend-ratio
This is a project of portfolio optimization using Quantum-inspired Tabu Search and Trend Ratio
Language:Python 3arawxx / PSO-demonstration
Demonstration of Particle Swarm Optimization (Auto Hyperparameter variant).
Language:Python 2KentaKato / SpyOpt
C++ implementation of the metaheuristic spy_algorithm. It can search for global optimal solutions for arbitrary non-convex functions.
Language:C++ 2lalit212212 / GBWPSO
Parallel Global Best-Worst Particle Swarm Optimization Algorithm for Solving Optimization Problems (Applied Soft Computing-2023)
Language:MATLAB 2luismescobarf / csp-prins-ts
Tabu Search algorithm for the Crew Scheduling Problem, using a modified Prins encoding.
Language:Python 2mateuszlesko / GenericAlgoirthm
Implementation of Generic Algorithm
Language:Java 2MichaelisTrofficus / pyheuristics
A toolkit for MetaHeuristics implemented in Python
Language:Python 2vintousan / dcp_param_selection_ga
Genetic Algorithm as an approach to select image restoration parameters that provides the greatest improvement to a turbid underwater image.
Language:Python 2
