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@ -5,7 +5,7 @@ It is lightweight and easy-to-use, and based on heuristics currently solving
- <a href="http://neo.lcc.uma.es/vrp/vrp-flavors/capacitated-vrp/" target="_blank">Capacitated VRP</a>
- <a href="http://neo.lcc.uma.es/vrp/vrp-flavors/multiple-depot-vrp/" target="_blank">Multiple Depot VRP</a>
- <a href="http://neo.lcc.uma.es/vrp/vrp-flavors/vrp-with-time-windows" target="_blank">VRP with Time Windows</a>
- <a href="http://neo.lcc.uma.es/vrp/vrp-flavors/vrp-with-backhauls/" target="_blank">VRP with Backhauls</a> (pickups and deliveries from and/to depot)
- <a href="http://neo.lcc.uma.es/vrp/vrp-flavors/vrp-with-backhauls/" target="_blank">VRP with Backhauls</a>*
- VRP with Heterogeneous Fleet
- Time-dependent VRP
- Various combination of these types
@ -17,6 +17,8 @@ Additionally, jsprit can be used along with <a href="http://www.matsim.org" targ
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.
*pickups and deliveries from and/to depot
##In Development
- continues improvement of code, handling and performance
- stable API to easily build algorithms from scratch