The CP-SAT Primer: Using and Understanding Google OR-Tools' CP-SAT Solver
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Updated
Oct 24, 2024 - Jupyter Notebook
The CP-SAT Primer: Using and Understanding Google OR-Tools' CP-SAT Solver
Algorithm for Cutting Stock Problem using Google OR-Tools. Link to the tool:
Track oriented, multi target, multi hypothesis tracker
Standard tools for workforce management, queuing, scheduling, rostering and optimization problems.
The tensorflow implementation of NIPS2016 paper "LightRNN: Memory and Computation-Efficient Recurrent Neural Networks" (https://arxiv.org/abs/1610.09893)
Using Google Operation Research Tools (Ortools) to solve complex scheduling problems (General optimization problems).
A webapp that visualizes and annotates your ortools' CP-SAT logs. Partially inspired by gurobi-logtools.
Unified API for multiple optimizer engines
Source code from AWS Lambda function that solves the Route Optimization problem, using Google Optimization tools
Simulation results of the paper: https://ieeexplore.ieee.org/document/9476848
A Constraint Programming solver for the Nurse Scheduling Problem, with personal shift preferences.
Operations Research in F#
Compute an optimized solution to the Vehicle Routing Problem with Time Windows using OR-Tools
WIP: Tune the hyperparameters of Google's OR-Tools' CP-SAT solver for specific models
Nomad Cyclist Problem - A variation of Traveling Salesman Problem (with open tour) adjusted for elevation and factors
This repository demonstrates how to solve the Vehicle Routing Problem (VRP) using OpenStreetMap data and OR-Tools library. The VRP is a classic optimization problem where a set of vehicles is tasked with visiting a set of locations while minimizing the total distance traveled.
Solves the Vehicle Routing Problem (VRP) using Column Generation (CG). It is made as an inspiration to use CG in more projects, since it can be quite effective in the right situations.
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