AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.
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Updated
Aug 19, 2025 - Java
AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.
Simple implementation of spatial skyline query algorithms
Java program to solve the 8 puzzle problem using branch and bound algorithm.
Command line tool for SAT solving, SMT solving in various theories (NRA, LRA, LIA, EQ, EQUF, BV)
🚀 Final Project Desain Analisis Algoritma (Divide and Conquer & Branch And Bound)
Java Travelling Salesman Problem (3 implementations)
TSP using Brute Force , Branch And Bound, Dynamic Programming, DFS Approximation Algorithm
Working on the Multiple Choice Knapsack Problem to design optimal packet schedulers for 5G data rates. (Jan - Feb 2020)
Knapsack Problem Solved Using Brute-Force, Backtrack and Branch and Bound Method for Algorithm Analysis Course in Telkom University
Theoretical analysis and implementation in Java of a Branch & Bound for the TSP that exploits the Langrangian relaxation of the 1-Tree to calculate the bounds efficiently.
A self-made demo for Advance Scheduling using branch and bound method
Branch and Bound Algorithm for the 0/1 Knapsack Problem using Lagrangian Relaxation
Combinatory Optimization Algorithms | Backtracking + Branch and Bound using Greedy approach | University Project
Travelling salesman problem: Artificial Inteligence, Computer Science, Middlesex University, London
Generate valid Magic square through branch and bound algorithm
Branch and bound implementation for flowshop permutation probleme (Séparation et évaluation )
A collection of Java implementations for algorithms and data structures.
BF, BnB and DP algorithms implementation for solving Travelling Salesman Problem. Academic project created at Wroclaw University of Science and Technology
All the programs that were developed in the DAA Lab
Exact solver for the Traveling Umpire Problem that uses a branch-and-bound algorithm with decomposition-based lower bounds, implementing the approach developed by T. Â. M. Toffolo (2017).
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