bio-inspired-optimization

There are 26 repositories under bio-inspired-optimization topic.

  • thieu1995/mealpy

    A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)

    Language:Python91515145188
  • Evolutionary-Intelligence/EC-A-Modern-Perspective

    Evolutionary Computation: A Modern Perspective ---> This is a free online book, which is actively updated now (1st Edition: from 2023 to 2027).

  • shahind/Nature-Inspired-Algorithms

    Sample Code Collection of Nature-Inspired Computational Methods

    Language:MATLAB474016
  • ngandng/NMOPSO

    An implementation of multi objective PSO for UAV path planning

    Language:MATLAB18112
  • ali-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.

  • Shahul-Rahman/SPGD-Search-Party-Gradient-Descent-algorithm

    SPGD: Search Party Gradient Descent algorithm, a Simple Gradient-Based Parallel Algorithm for Bound-Constrained Optimization. Link: https://www.mdpi.com/2227-7390/10/5/800

    Language:Jupyter Notebook8401
  • ali-ece/IPO-Inclined-Planes-system-Optimization-Algorithm

    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:MATLAB6111
  • vkotiyal/thesis-ecs-codes

    Python code for ECS-NL.

    Language:Jupyter Notebook6201
  • ali-ece/A-Modified-Inclined-Planes-system-Optimization-MIPO-Algorithm

    With the aim of create a powerful trade-off between the concepts of exploitation and exploration, and rectify the complexity of their structural parameters in the standard IPO, a modified version of IPO (called MIPO) is introduced as an efficient optimization algorithm for digital infinite-impulse-response (IIR) filters model identification. The MIPO utilizes an appropriate mechanism based on the executive steps of algorithm with the constant damp factors.

    Language:MATLAB4101
  • mbalchanowski/Krill-Herd

    Simple console implementation of the Krill Herd (KH) algorithm

    Language:C#3200
  • adlyZaroui/metaheuristics-benchmark

    Python3 framework for comparative study of recent metaheuristics

    Language:Jupyter Notebook1100
  • ali-ece/A-Simplified-and-Efficient-Version-of-Inclined-Planes-system-Optimization-SIPO-Algorithm

    A simplified and effective version of IPO (called SIPO) with the aim of simplifying the main IPO equations, creating a powerful trade-off between the concepts of exploitation and exploration, and modifying the complexity of their structural parameters.

    Language:MATLAB1101
  • FTVarna/AHPSO

    AHPSO: Altruistic Heterogeneous Particle Swarm Optimisation Algorithm. Source code for the paper: IEEE SSCI https://ieeexplore.ieee.org/document/9660149

    Language:MATLAB1100
  • George614/BioAlgorithms

    Coursework for CSCI-633 Bio-Inspired Intelligent Systems

    Language:Python1100
  • Impelon/ant-image-seg

    An ant colony optimization program for solving image segmentation created in the context of IT3708 at NTNU.

    Language:Rust1200
  • lucasromulosr/Bioinspired-Algorithms

    Study and implementation of bioinspired metaheuristics (ACO, CLONALG, GA, PSO)

    Language:Python1100
  • matiascr/bia

    Bio inspired algorithms in Elixir

    Language:Elixir1100
  • zaha2020/Bio_Inspired_Computing

    This repository contains my Bio-Inspired Computing Projects during University and the projects that I've implemented due to my interest in Bio-Inspired Computing. These projects include l-systems development and bio-inspired optimization methods.

    Language:Jupyter Notebook1100
  • ali-ece/Multi-Objective-Inclined-Planes-system-Optimization-MOIPO-

    Multi-objective optimization based on sloping plate optimization algorithm called Multi-objective Inclined Planes system optimization algorithm (MOIPO) is presented in this link. The proposed method uses the concept of Pareto optimization to identify non-dominant positions and an external tank to maintain these positions.

  • FTVarna/BEPSO

    BEPSO: Biased Eavesdropping Particle Swarm Optimisation Algorithm . Source code for the paper: IEEE SSCI https://ieeexplore.ieee.org/document/9660113

    Language:MATLAB00
  • geldas/VBC

    Bio-inspired Computing

    Language:Python0200
  • harshal-vaze/Ant-Colony-Optimization-for-Path-Planning-using-Rule-based-in-Dynamic-and-Complex-Environment

    In this project, a new ACO algorithm is proposed which ensures to solve the problems encountered in traditional ACO algorithms. This algorithm was tested on number of environments to examine efficiency, error margin and count computational time. The results ensured that the proposed ACO algorithm is completely efficient in small-scale environments and remarkably similar results were observed on testing it on the bigger-scale environment. The evaluations prove that the Ant Colony Optimization algorithm for path planning can provide rapid path planning with acceptable results and for future development can be integrated with the robot system to test in the real world scenarios.

  • Martasil/Genetic_alg_generalizations_EMP_knapsack

    Source code for the thesis entitled "Teoría de la aproximabilidad: análisis teórico y resolución práctica mediante algoritmos genéticos."

    Language:Python0100
  • simeeid/IT3708_bio-inspired_AI_24

    Projects in IT3708 bio-inspired AI, a second degree level subject at NTNU, 2024

    Language:Java0100
  • albertoxamin/bio-slicing-for-3d-printing

    Since 3d printing is a long process, using bio-inspired algorithms to obtain the model that requires less support material and/or prints in less time

    Language:Python301
  • selcia25/bio-inspired-optimization-techniques

    🧬This repository contains implementations of various bio-inspired optimization algorithms, along with example notebooks and resources for demonstration.

    Language:Jupyter Notebook10