# Solving Travelling Salesman Problem

We started with a 2-opt heuristic since it is extremely easy to understand and implement.The running time is good too, A visualization on Youtube might be interesting for getting a better understanding.We start with a Nearest neighbour path, where we pick the closest point from each point in the path as the next point.

We started with a 2-opt heuristic since it is extremely easy to understand and implement.The running time is good too, A visualization on Youtube might be interesting for getting a better understanding.We start with a Nearest neighbour path, where we pick the closest point from each point in the path as the next point.

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It is documented in TSPLIB’s (a popular TSP Solver library) documentation.The entire process is realtime and happening in an Android smartphone.Testing our heuristic We want to analyse how good our heuristic works on all the data collected till date by Lean Agri.Which means we are looking at a Euclidean Travelling Salesman Problem.Here’s an explanation which I will just quote from this source: An interesting special case of the TSP is to consider the optimal route passing through a collection of n points (sites) in the Euclidean plane (or more generally, n-dimensional Euclidean space).We at Lean Agri believe that software should be adaptive of the user rather than the other way round.We build solutions which allow users to improve their efficiency of working rather than training them to efficiently use the software we build.We have mapped 1000 farmers all with farms of different shapes and sizes.We run our TSP algorithm against all the farm mappings collected till date, and we see that around 15% of the results with our TSP setup fails to match.The first attempt was to try and arrange all vertices in a cyclic order to create a Polygon.The algorithm is very easy, we take a reference point and arrange all points in an increasing order of angles relative to that point.

## Comments Solving Travelling Salesman Problem

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