A research protocol for deep graph matching.

Python library for finding the optimal transformation(s) that makes two matrices as close as possible to each other.

A Multiple-population coarse-grained Genetic Algorithm to solve the Quadratic Assignment Problem

Solution quadratic assign problem via LS(local search), ILS(iterated local search), GLS(guided local search)

This is a Python implementation of the Doubly Stochastic Projected Fixed Point (DSPFP) algorithm for solving the Quadratic Assignment Problem / Graph Matching..

The research work on local search algorithms

Algorithms for solving the Quadratic Assignment Problem

Heuristics for the Quadratic Assignment Problem (QAP) - R package

Unofficial implemnetation of "Solving Quadratic Assignemt Problem using Deep Reinforcement Learning" (https://arxiv.org/abs/2310.01604)

Implementation of different algorithms: heuristic search, Simulated Annealing, Ant Colony Algorithm and Tabu Search to a Quadratic Assignment Problem.

Algorithms for solving the quadratic assignment problem (QAP) implemented in Julia.

Applications of Metaheuristic Optimization in Python

Mapping and routing of a data flow network mapped on an mesh NoC

Solving quadratic assignment problem using iterated local search, improved hybrid genetic algorithm, tabu search, and constraint solving.

A simple Quadratic Assignment Problem solver using heuristics and metaheuristics

This package supports general, orthogonal, rotation, permutation, projection, and symmetric Procrustes problems, including both the normal one-sided approach and (for orthogonal and permutation Procrustes) two-sided approaches, where both the rows and columns are transformed.

laboratory works for combinatoric optimization course

Quadratic Assignment Problem, an Enhanced Solver

Projects of "Bio Inspired Computing" Course - University of Tehran - Spring 2024

This is the official code for the AISTATS 2023 paper "Learning Constrained Structured Spaces with Application to Multi-Graph Matching"