Bin Packing Problem using Neural Combinatorial Optimization.

Leverage the power of modern C++ to build robust and scalable applications

Julia and Python recursion algorithm, fractal geometry and dynamic programming applications including Edit Distance, Knapsack (Multiple Choice), Stock Trading, Pythagorean Tree, Koch Snowflake, Jerusalem Cross, Sierpiński Carpet, Hilbert Curve, Pascal Triangle, Prime Factorization, Palindrome, Egg Drop, Coin Change, Hanoi Tower, Cantor Set, Fibo…

Evolutionary Algorithm for the 2D Packing Problem combined with the 0/1 Knapsack Problem (Master Thesis)

Auto Parallelization - runs test files in multiple jobs

Algorithms for solving knapsack problems with Python

An example of how to run Rails CI and test steps in parallel with Docker and Buildkite

Julia package to solve Knapsack problems

Exact and meta-heuristic algorithms for NP problems

A module for resource allocation solving

Evolutionary Multitasking in Permutation-Based Combinatorial Optimization Problems: Realization with TSP and Knapsack

Knapsack algorithms

All DSA-2 topics are covered in the UIU DSA-2 course, including both lab and theory courses. Check DSA-1 Topics: https://github.com/TashinParvez/DSA_1_UIU

Solution implementation for HackerRank's Array-Subsets problem.

This repository was created for the subject of Computer Theory. The propose of this subject is to improve your skills to solve the 0-1 knapsack problem of different ways. The techniques used were Dynamic Programing and two metaheuristics (which are GRASP and TABU search).

Classical algorithm implementation.

Knapsack Problem implemented in Python. This includes a Linear Greedy and Quadratic Knapsack Implementation.

My team's Hash Code 2020 solutions

An example of how to run Rails CI and test steps in parallel with Buildkite

This repository contains a C++ program that solves the Knapsack Problem using a Genetic Algorithm. The Knapsack Problem is a classic optimization problem where we aim to maximize the total value of items to be packed in a knapsack, given the knapsack's weight capacity and a set of items with their respective weights and values.