1
0
Fork 0
mirror of https://github.com/graphhopper/jsprit.git synced 2020-01-24 07:45:05 +01:00
No description
Find a file
2014-01-08 15:32:40 +01:00
jsprit-analysis eliminate "maven-enforcer-plugin (goal "enforce") is ignored by m2e" 2013-12-19 10:42:20 +01:00
jsprit-core Merge branch 'master' of https://github.com/jsprit/jsprit 2014-01-06 12:57:22 +01:00
jsprit-examples eliminate "maven-enforcer-plugin (goal "enforce") is ignored by m2e" 2013-12-19 10:42:20 +01:00
jsprit-instances eliminate "maven-enforcer-plugin (goal "enforce") is ignored by m2e" 2013-12-19 10:42:20 +01:00
.gitignore rm .DS_Store files and add them to .gitignore 2013-06-06 11:00:07 +02:00
.project clean 2013-06-04 14:43:49 +02:00
CHANGELOG.md update according to v1.0.0 2013-11-26 15:04:08 +01:00
license.txt add license.txt prj-head and license-head to latest example 2013-11-26 17:15:57 +01:00
pom.xml eliminate "maven-enforcer-plugin (goal "enforce") is ignored by m2e" 2013-12-19 10:42:20 +01:00
README.md Update README.md 2014-01-08 15:32:40 +01:00

jsprit

jsprit is a java based, open source toolkit for solving rich

rich is rich
traveling salesman (TSP) and vehicle routing problems (VRP). It is lightweight, flexible and easy-to-use, and based on a single all-purpose meta-heuristic currently solving

  • Capacitated VRP
  • Multiple Depot VRP
  • VRP with Time Windows
  • VRP with Backhauls
  • VRP with Pickups and Deliveries
  • VRP with Heterogeneous Fleet
  • Time-dependent VRP
  • Traveling Salesman Problem
  • Dial-a-Ride Problem
  • Various combination of these types

Setting up the problem, defining additional constraints, modifying the algorithms and visualising the discovered solutions is as easy and handy as reading classical VRP instances to benchmark your algorithm. It is fit for change and extension due to a modular design and a comprehensive set of unit and integration-tests.

Additionally, jsprit can be used along with MATSim to solve the above problem-types in real networks (i.e. without preprocessing transport times and costs). A variety of least cost path algorithms such as Dijkstra and A* can be used, and a dynamic and interactive visualiser greatly enhances the analysis.

##In Development

  • continues improvement of code, handling and performance
  • soft constraints
  • various capacity dimensions and multiple time-windows
  • large scale instances

##Documentation

Please visit jsprit-wiki to learn more.

##License This software is released under LGPL.

##Get Started

####You know Maven and have an IDE

Add the latest snapshot (i.e. head of development) to your pom.

Add the latest release to your pom.

####If not

The following documentation is recommended:

GeoTools - Quickstart

Here you learn to setup the Java environment and an Integrated Development Environment (IDE). In the subsection Adding Jars to your Project you learn to integrate external libraries in your project. Just copy/paste the above jsprit releases/snapshots to your pom.xml instead of the GeoTools-artifacts.

##About The jsprit-project is created and maintained by Stefan Schröder. It is motivated by two issues.

First, there is an almost endless list of papers and algorithms to tackle vehicle routing problems, BUT there are (as far as I know) only a very few open source implementations of one of these thousands algorithms.

Second, it is motivated by my PhD-project at KIT where I apply vehicle routing algorithms to solve behavioural models of freight agents to assess (freight) transport policy measures.

It is mainly inspired by my research group at KIT-ECON, and by an awesome open-source project called MATSim and its developers.

If you have questions or if you use jsprit, it would be great you give feedback and let me know your experience:

Email: jsprit.vehicle.routing@gmail.com