shubhampachori12110095 Goto Github PK

vdcnn

Tensorflow and Keras Implementation of Very Deep Convolutional Neural Network for Text Classification

vde

Variational Autoencoder for Dimensionality Reduction of Time-Series

veegan

VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning

vega-lite

A concise grammar of interactive graphics, built on Vega.

vehcile-routing-problem-with-time-window-constraints

Solving Vehicle Routing Problem with Time Window constraint using Kmeans clustering algorithm

vehicle-assignment-and-routing-

Automating and Optimizing manager's task of allotting and planning schedule/time-table for service providers.

vehicle-route-optimisation

Solving VRP problem using ORTOOLS routing library

vehicle-routing

Solving the Vehicle Routing Problem using Discrete Optimization Techniques

vehicle-routing-1

Column generation

vehicle-routing-2

Vehicle Routing with Time Windows (VRPTW) example with added skill sets, continuous planning, real road distances, and kie server integration

vehicle-routing-3

Vehicle Routing Pickup-Delivery scheduling is implemented, which used a meta-heuristic algorithm known as Tabu Search to determine the most efficient route for each vehicle.

vehicle-routing-optimization

Solver for vehicle routing problem(VRP)

vehicle-routing-problem

A Vehicle Routing Problem optimized solution with Variable Neighborhood Search (VNS), Variable Neighborhood Descent (VND) and Simulated Annealing

vehicle-routing-problem-1

Repository for solving the Vehicle Routing Problem (VRP) with Ant colony algorithm

vehicle-routing-problem-2

Solution for multiple depot vehicle routing problem using Ant Colony Optimization.

vehicle-routing-problem-vrp-clarke-wright-savings-method

Clark-Wright Savings algorithm for Vehicle Routing Problem (VRP) with single depot and vehicle capacity constraints.

vehicle-routing-problem-vrp-optimisation

Determining the optimal solution for a Travelling Salesman Problem (TSP) using Heuristic and Meta-Heuristic algorithms.

vehicle-routing-problem-vrp-with-time-window

The Vehicle Routing Problem with Time Windows (VRPTW) is the extension of the Capacitated Vehicle Routing Problem (CVRP) where the service at each customer must start within an associated time interval, called a time window. Time windows may be hard or soft. In case of hard time windows, a vehicle that arrives too early at a customer must wait until the customer is ready to begin service. In general, waiting before the start of a time window incurs no cost. In the case of soft time windows, every time window can be violated barring a penalty cost. The time windows may be one-sided, e.g., stated as the latest time for delivery. Time windows arise naturally in problems faced by business organizations which work on flexible time schedules. Specific problems with hard time windows include security patrol service, bank deliveries, postal deliveries, industrial refuse collection, grocery delivery, school bus routing, and urban newspaper distribution. Among the soft time window problems, dial-a-ride problems constitute an important example.

vehicle-routing-problem-with-backhaul

Vehicle Routing Problem with Backhaul (VRPB); Open vehicle routing problem; Lagrangian decomposition; Lagrangian relaxation algorithm; Clustering algorithm; CPLEX optimization solver; Python implementation

vehicle-routing-problem-with-flexible-delivery-locations

Vehicle Routing Problem with Flexible Delivery Locations

vehicle-routing-problem-with-pickup-and-delivery

vehicle-routing-problem-with-time-windows

vehicle-routing-problems

vehicle-routing-reinforcement-learning

Vehicle Routing using Actor-Critic Reinforcement Learning and RNN decoder

vehicle-routing-reinforcement-learning-ppo

vehicle routing reinforcement learning proximal policy optimization

vehicle-routing-viz

A vehicle routing visualisation system with node.js and Google Maps API

vehiclerouting

Takes a JSON with delivery time periods and objectives and routes them

vehiclerouting-1

vehiclerouting-2

This repository contains the code written for my adventures into solving vehicle routing problems with Reinforcement Learning, Competitive Coevolution, the Clarke-Wright Savings Algorithm, a Nearest Neighbour Heuristic, and the PULP Linear Programming library

vehicleroutingproblem

Vehicle Routing Problem for Operations Optimization