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A project on improving Neural Networks performance by using Genetic Algorithms.
A-List of all the Assignment done in Artificial Intelligence Course @IIIT-D
Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.
:seedling: Genetic Algorithm, Memetic Algorithms, GRASP, Simulated Annealing, Multi start search, Reiterated Local Search, Local Search, Greedy and randomized Greedy
Convolutional Genetic Programming method for image classification
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)
This project proposes an efficient memetic algorithm for the graph coloring problem. Authors : L. Moalic (laurent.moalic@uha.fr) and A. Gondran (alexandre.gondran@enac.fr). Details are presented in the paper "Variations on memetic algorithms for graph coloring problems" :
Implementation of Genetic Algorithm, Memetic Algorithm and Constraint Satisfaction on a Time Table scheduling problem. Also has an implementation of MiniMax Strategy for TicTacToe
A Bionomic Algorithm for the Aircraft Landing Problem
:briefcase: Approach to the Quadratic Assignment Problem in C++ using memetic algorithms and tabu search.
Implementation about a memetic algorithm, including a genetic algorithm and local search for our defined Minesweeper game.
Shuffled Complex Evolution (SCE-UA) in MATLAB
All the programming assignments done as a part of the AI course in IIIT Delhi
Solving N-Queens problem by implementing Memetic Algorithm.
🧠 A set of metaheuristics applied in solving the QAP problem, including local search, genetic algorithms, memetics and more.
Memetic Algorithms with Explicit Diversity Management for the Linear Ordering Problem.
This is an implementation for solving the TSP problem using a genetic and a memetic algorithm. PySpark is used to use a distributed workload.
This work was aimed at finding methods to identify the most distant proteins and most diverse subsets of proteins from large protein databases in a scalable and efficient way using a dataset of protein embeddings from SwissProt, data mining techniques and metaheuristics.
Shuffled Frog Leaping Algorithm (SFLA) in MATLAB
The implementation of the paper Solving the Latin Square Completion Problem by Memetic Graph Coloring
C++ implementation of Memetic Algorithm
Second Year project (Module: Artificial Intelligence Methods), focusing on implementing and evaluating AI Optimisation methods.
Metaheuristics for finding good Low Autocorrelation Binary Sequences.
Detection of epistasis patterns using Memetic algorithm and Path Relinking method
Symmetric Cipher Breaking Using Genetic and Memetic Algorithms
CUDA code for DE+PSO for Gene Regulatory Network inference
COM 3031 Computational Intelligence Assignment
Evolutionary Algorithms in Scala