Difference between revisions of "Algorithm"
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Routing multiple addresses is quite a puzzle. With 20 destinations the from-to travel times matrix has roughly 20 x 20 = 400 elements. The number of possible routes is even bigger, approximately 20 x 19 x 18 x ... x 3 x 2 x 1 = 2,432,902,008,176,640,000. | Routing multiple addresses is quite a puzzle. With 20 destinations the from-to travel times matrix has roughly 20 x 20 = 400 elements. The number of possible routes is even bigger, approximately 20 x 19 x 18 x ... x 3 x 2 x 1 = 2,432,902,008,176,640,000. | ||
| − | Mathematicians call it a "hard" problem and there is no final one-size-fits-all solution available. They even have a name for it: ''The Travelling Salesman Problem''. Indeed, humans can fly to the moon, but | + | Mathematicians call it a "hard" problem and there is no final one-size-fits-all solution available. They even have a name for it: ''The Travelling Salesman Problem'' (TSP). Indeed, humans can fly to the moon, but in math there is no ultimate answer to this problem. |
Learn more: https://en.wikipedia.org/wiki/Travelling_salesman_problem | Learn more: https://en.wikipedia.org/wiki/Travelling_salesman_problem | ||
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| + | Operations Research researchers however have found some very good methods. Our algorithm is an effective implementation that finds the optimal route in most cases. But it is an algorithm for matter of speed that does not guarantee optimality. | ||
Revision as of 14:36, 11 June 2016
The RouteXL planning algorithm uses travel times and a optimization method to minimize total travel time.
Travel times
To find the best route, the travel times between all locations are required. While most other route optimization tools use geographic distances (as the crow flies), RouteXL uses a crowdsourced road network. OpenStreetMap is the free Wiki World Map, an openly licensed map of the world being created by volunteers using local knowledge, GPS tracks and donated sources.
Learn more: https://www.openstreetmap.org/
Optimization
Routing multiple addresses is quite a puzzle. With 20 destinations the from-to travel times matrix has roughly 20 x 20 = 400 elements. The number of possible routes is even bigger, approximately 20 x 19 x 18 x ... x 3 x 2 x 1 = 2,432,902,008,176,640,000.
Mathematicians call it a "hard" problem and there is no final one-size-fits-all solution available. They even have a name for it: The Travelling Salesman Problem (TSP). Indeed, humans can fly to the moon, but in math there is no ultimate answer to this problem.
Learn more: https://en.wikipedia.org/wiki/Travelling_salesman_problem
Operations Research researchers however have found some very good methods. Our algorithm is an effective implementation that finds the optimal route in most cases. But it is an algorithm for matter of speed that does not guarantee optimality.
