Timefold Solver is an AI constraint solver for Python to optimize the Vehicle Routing Problem, Employee Rostering, Maintenance Scheduling, Task Assignment, School Timetabling, Cloud Optimization, Conference Scheduling, Job Shop Scheduling, Bin Packing and many more planning problems.

Adaptive Heterogeneous Improved Dynamic Multi-Swarm PSO (A-HIDMS-PSO) Algorithm

Open-source framework for adaptive manufacturing processes scheduling

This project implements two nature-inspired optimization algorithms: Moth Flame Optimization (MFO) and Honey Badger Optimization (HBO). Both algorithms are designed to solve complex optimization problems by mimicking behaviors observed in nature. also it includes a path finding algorithm, A-star

This research proposes a novel order batching approach for warehouses to minimize total tardiness, considering category, weight, and fragility constraints. A Set-based Mayfly Algorithm (SBMA) is developed, adapting the Mayfly Algorithm to the discrete problem and leveraging swarming/mating behaviors to avoid local optima.

Hiperheurísticas: Aplicación a problemas de asignación de horario y metaoptimización

Meta-Heuristics vs Backpropagation: A Fresh Look at CNN Model Parameter Optimization for Image Classification

Search for a model and corresponding hyperparameters that best model your data

TSP - Ant Colony Optimization

Travel Salesman Problem Optimization using Genetic Algorithm. Read the Report for complete understanding.

This Python package provides implementations of three metaheuristic algorithms to solve the Traveling Salesman Problem (TSP): Steepest Ascent Hill Climbing, Simulated Annealing, and Ant Colony Optimization.

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 ser…

A tool to automatic design Multiple-Stub Matching Networks (MSMN) for wideband on Transmission Lines, using Metaheuristics Optimization Algorithms.

Implementation of the tabu search algorithm used in my thesis. The problem in the thesis is political districting.

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:…

Solving Travelling Salesman Problem examples using the Simulated Annealing and Taboo Search approaches and comparing the results.

Applying evolutionary metaheuristic algorithms to solve Travelling Salesman Problem.

Implementation of the GSA Algorithm for seminar of Soft_Computing Course at University of Kerman, Fall 2023

Large suite of algorithms for black-box optimization in C++ with python wrappers.