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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).
Implementation of a genetic algorithm to solve the Knapsack problem with a capacity C and a given set of N objects. The genetic fitness function sums up the profits of the objects in the Knapsack.
Explore the Knapsack algorithm in action with this TypeScript implementation that optimizes transaction selection based on account balances. This repository demonstrates how the Knapsack algorithm can be utilized to choose transactions that yield maximum value while adhering to account balance constraints.
This is an implementation of the 0-1 knapsack problem in C using dynamic programming. The problem consists of a set of items, each with a weight and a value, and a knapsack with a maximum weight capacity. The goal is to determine the subset of items that maximizes the total value of the knapsack without exceeding its weight capacity.
C++ Algorithms and data structures using only standard libraries. This answers many of the challenges in Codility and HackerRank. > 1200 Google Test cases and counting.
About InvestKuy aims to bridge the gap between investors and efficient financial decision-making by leveraging advanced algorithms. Designed with both novice and experienced investors in mind, InvestKuy offers a seamless and intuitive platform for optimizing investment portfolios. The system analyzes your risk tolerance and investment goals, then