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.
🌱 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
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" :
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:…
Time Series Segmentation Algorithms
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
💼 Approach to the Quadratic Assignment Problem in C++ using memetic algorithms and tabu search.
Shuffled Complex Evolution (SCE-UA) in MATLAB
Implementation about a memetic algorithm, including a genetic algorithm and local search for our defined Minesweeper game.
Solving N-Queens problem by implementing Memetic Algorithm.
All the programming assignments done as a part of the AI course in IIIT Delhi
Shuffled Frog Leaping Algorithm (SFLA) in MATLAB
🧠 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.
A genetic algorithm to solve the traveling salesman problem
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