A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

dnn_opt is a machine learning library to perform optimization and neural network training by using meta-heuristics with multi-core and GPU support

Complete pipeline to design, optimize and view 2D kinematic mechanisms in Python

A ray-based library of Distributed POPulation-based OPtimization for Large-Scale Black-Box Optimization.

(Code) A new workload prediction model using extreme learning machine and enhanced tug of war optimization

HGJO: An improved golden jackal optimization for Otsu’s method based multilevel image thresholding

Machine Learning Hyper-parameter Tuning processes

Implementation of a solution to Jdata GOC

VNS-SOLVER : implementation of the VNS meta-heuristic using the C programming language

Techniques and applications of optimisation in operations research, including linear programming, integer programming, dynamic programming and meta-heuristics. Use of Python and the Gurobi optimisation package for linear and integer programming.

Efficient Time-series Forecasting using Neural Network and Opposition-based Coral Reefs Optimization

Online selection hyper-heuristic with generic parameter control in low-level heuristics (meta-heuristic).

Meta-heuristic approaches to select important features only for performance enhancement in effective Intrusion Detection System.

🤖 This project develops an autonomous Hex player that analyzes an NxN board and selects optimal moves using AI. The agent inherits from the base Player class, evaluates the game state on each turn, and returns the best action without storing global state or external dependencies.

Julia library for the Determinant-Optimality Problem (D-OPT)

(Code IQSO-MLP) nQSV-Net: a novel queuing search variant for global space search and workload modeling

Coursework for CSCI-633 Bio-Inspired Intelligent Systems

Multi-Objective Agent-Based Hyper-Heuristic

Master Thesis for M.Sc. Business Education - Pre-Trained Denoising Autoencoders Long Short-Term Memory Networks as probabilistic Models for Estimation of Distribution Genetic Programming