Lulustudy1's starred repositories
LargeNeighbourhoodSearch
Large Neighbourhood Search (Shaw) for VRPTW
pyCombinatorial
A library to solve the TSP (Travelling Salesman Problem) using Exact Algorithms, Heuristics and Metaheuristics : 2-opt; 2.5-opt; 3-opt; 4-opt; 5-opt; 2-opt Stochastic; 2.5-opt Stochastic; 3-opt Stochastic; 4-opt Stochastic; 5-opt Stochastic; Ant Colony Optimization; Bellman-Held-Karp Exact Algorithm; Branch & Bound; BRKGA (Biased Random Key Genetic Algorithm); Brute Force; Cheapest Insertion; Christofides Algorithm; Clarke & Wright (Savings Heuristic); Concave Hull Algorithm; Convex Hull Algorithm; Elastic Net; Extremal Optimization; Farthest Insertion; Genetic Algorithm; GRASP (Greedy Randomized Adaptive Search Procedure); Greedy Karp-Steele Patching; Guided Search; Hopfield Network; Iterated Search; Karp-Steele Patching; Multifragment Heuristic; Nearest Insertion; Nearest Neighbour; Random Insertion; Random Tour; Scatter Search; Simulated Annealing; SOM (Self Organizing Maps); Space Filling Curve (Hilbert); Space Filling Curve (Morton); Space Filling Curve (Sierpinski); Stochastic Hill Climbing; Sweep; Tabu Search; Truncated Branch & Bound; Twice-Around the Tree Algorithm (Double Tree Algorithm); Variable Neighborhood Search.
geographical-search-rescue-AI
Search and Rescue AI solution using K-means Clustering, VRP (Vehicle Routing Problem), Frame Allocation and Hungarian Algorithm.
Supplement_ALNS_TDGVRPTW
The supplement contains the algorithm code and instances as a complement of the paper "Efficient Feasibility Checks and an ALNS Algorithm for the TDGVRPTW"
alns-framework-for-evsp
An ALNS framwork for solving EVSP written in Python.
Java-VRPTW-ALNS-
Solving the VRPTW problem using the ALNS algorithm in Java
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)
adaptive-large-neighbourhood-search
ALNS header-only library (loosely) based on the original implementation by Stefan Ropke.
LRP-for-garbage-collection
Two-Echelon Capacitated location-routing problem of Heterogeneous fleets
ALNS-VRPTW-FL
Adaptive Large Neighborhood Search (ALNS) for the Vehicle Routing Problem with Time Windows, Flexible Service Locations and Time-dependent Location Capacity.
Vechicle-Routing-Problem-VRP-with-Pickup-and-Delivery
Pickup-and-Delivery Problems (PDPs) constitute an important family of routing problems in which goods or passengers have to be transported from different origins to different destinations. These problems are usually defined on a graph in which vertices represent origins or destinations for the different entities (or commodities) to be transported. PDPs can be classified into three main categories according to the type of demand and route structure being considered. In many-to-many (M-M) problems, each commodity may have multiple origins and destinations and any location may be the origin or destination of multiple commodities. These problems arise, for example, in the repositioning of inventory between retail stores or in the management of bicycle or car sharing systems. One-tomany- to-one (1-M-1) problems are characterized by the presence of some commodities to be delivered from a depot to many customers and of other commodities to be collected at the customers and transported back to the depot. These have applications, for example, in the distribution of beverages and the collection of empty cans and bottles. They also arise in forward and reverse logistics systems where, in addition to delivering new products, one must plan the collection of used, defective, or obsolete products. Finally, in one-to-one (1-1) problems, each commodity has a single origin and a single destination between which it must be transported. Typical applications of these problems are less than- truckload transportation and urban courier operations.
location-routing
A state-of-the-art exact Branch-Cut-and-Price algorithm for the Capacitated Location-Routing Problem and related problems
OR_location_routing_problem_study
Facility Location and routing problems: Survey, Models and Algorithm
electric_vehicle_routing_problem_with_time_windows
Electric-Vehicle Routing Problem with Time Windows (EVRPTW) for the optimization in transports and logistics coure summer term 2018 at the technical university of vienna
Reprinted_Applied_Energy
复刻论文Applied Energy的论文A bi-layer optimization based temporal and spatial scheduling for large-scale electric vehicles，包含考虑电动汽车有序充放电的机组组合和最优潮流
Electric-Vehicle-Optimal-Charging
The python codes implement the EV charging problem as static and dynamic optimization problem. The optimizers try to maximize the revenue and minimize the cost of the EV charging plant.
ElectricalVSP-ColumnGeneration
Companion code for "Electric Vehicle Fleets: Scalable Route and Recharge Scheduling through Column Generation" by Parmentier, Martinelli and Vidal
GOC-EVRPTW
JD 城市物流运输车辆智能调度
Online-3D-BPP-DRL
This repository contains the implementation of paper Online 3D Bin Packing with Constrained Deep Reinforcement Learning.
3dbinpacking
A python library for 3D Bin Packing
PYTHON_Genetic_Simulated_Annealing_TabuSearch_Algorithms
The work consists of the implementation of three metaheuristic approaches - based on simulated annealing, tabu research, genetic algorithms, particle swarm optimization or differential evolution - to solve each of these problems (1) and (2).