Vehicle Routing Problems with Time Windows and
Multiple Service Workers
Customer Clustering
Gerald Senarclens de Grancy
<gerald@senarclens.eu>,
Dagmar Tschabrun <dagmar.tschabrun@edu.uni-graz.at>,
Marc Reimann <marc.reimann@uni-graz.at>
YAMS, December 2013, Salzburg
Delivery of soft drinks to small and medium sized retailers in São Paulo:
The objective of our current research is to identify good heuristics for creating customer clusters that can be efficiently serviced by as few trucks and workers as possible (minimize the objective function of the outer VRPTWMS).
The clustering consists of assigning customers to parking locations and determining a schedule for servicing the assigned customers.
{ "name": "presentation 3", "description": "This instance is for presentation/ demo purposes. It can also be used to test the efficiency of algorithms as it is designed with an optimal solution in mind. It can be solved with three trucks - one with one, the second with two and the third with three service workers. Parking at the customer sites is forbidden by an extremely high penalty.", "truckCapacity": 100.0, "costTruck": 1.0, "costWorker": 0.1, "costDistance": 0.0001, "bestKnownTrucks": 3, "bestKnownWorkers": 6, "bestKnownDistance": 410.9302842022, "bestKnownCost": 3.6410930284, "bestKnownSolution": "3;0;1,6,10;2,5;3,8,12,11,14;4,9,13,7;0 2;0;15,21,27,23,30;18,28,25,24;16,20,26;19,22;17,29;0 1;0;31,47,43;35,40;32,45,49;36,41;31,48;33,46,42,44;0", "optimumKnown": true, "depot": { "id": 0, "x": 0.0, "y": 0.0, "est": 0.0, "lst": 480.0}, "parkings": [ { "id": 1, "x": -29, "y": -31 }, ... { "id": 39, "x": -1, "y": 36 } ], "clients": [ { "id": 5, "x": -39, "y": -9, "demand": 10, "est": 0, "lst": 240, "st": 5 }, ... { "id": 49, "x": 53, "y": -9, "demand": 10, "est": 0, "lst": 480, "st": 5 } ] }