zhangsir11122's starred repositories
Max-Clique-Cplex-Python
Maximum Clique Problem solved by Branch and Bound method and Cplex Optimization.
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
Facility-Location-in-Genetic-Algorithm
This project use genetic algorithm to solve the facility location problem in matlab.
Facility_Location
This repository contains resources for Facility Location and Location Allocation. It is intended for research and educational use. Nothing within this repository may be used for commercial activities.
facility-location-gurobi
Exact approach to solve the facility location problem with Gurobi.
Facility-Location-Problem-with-DoCplex
通过docplex工具对选址问题求解
OR_location_routing_problem_study
Facility Location and routing problems: Survey, Models and Algorithm
Validate-VRPTW-Model-with-Gurobi
python calls Gurobi to verify the correctness of VRPTW model
OUTPUT-ALNS-Java-Python-code-and-Samples
help yourself~
ALNS_VRPTW
Adaptive large neighbourhood search (ALNS) algorithm for vehichle routing problem with time windows (VRPTW)
IMOLEM-for-VRPSD
An Improved Learnable Evolution Model for Solving Multi-Objective Vehicle Routing Problem with Stochastic Demand
multiobjective_route_optimisation
This code optimises a three-objective traveling salesman problem (TSP). Three different multi-objective evolutionary algorithms (MOEAs) are used to solve this problem. The applied MOEAs are NSGA-II, MOEA/D, and IBEA which are taken from the Platypus framework..
NSGA-II
This is a python implementation of NSGA-II algorithm. NSGA is a popular non-domination based genetic algorithm for multi-objective optimization. It is a very effective algorithm but has been generally criticized for its computational complexity, lack of elitism and for choosing the optimal parameter value for sharing parameter σshare. A modified version, NSGA II was developed, which has a better sorting algorithm , incorporates elitism and no sharing parameter needs to be chosen a priori.
trucks-and-drones
Using reinforcement learning to solve the travelling salesman and vehicle routing problem with drones (or robots).
TSPDrone-RL
A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone
mFSTSP-VDS
Test problems and heuristic pseudo-code for solving the Multiple Flying Sidekicks Traveling Salesman Problem with Variable Drone Speeds (mFSTSP-VDS)
Drones-TSP
Code for the Travelling Salesman Problem with Drone
TSP-D-Instances
A repository with instances for the TSP with Drones
TSP-D-algorithms
Python codes for Traveling Salesman Problem with Drone (TSP-D)
Huristic-code
Some heuristic code for combination problem