Abstract
Traveling Salesman Problem (TSP) is an optimization to find the shortest path to reach several destinations in one trip without passing through the same city and back again to the early departure city, the process is applied to the delivery systems. This comparison is done using two methods, namely optimization genetic algorithm and hill climbing. Hill Climbing works by directly selecting a new path that is exchanged with the neighbour’s to get the track distance smaller than the previous track, without testing. Genetic algorithms depend on the input parameters, they are the number of population, the probability of crossover, mutation probability and the number of generations. To simplify the process of determining the shortest path supported by the development of software that uses the google map API. Tests carried out as much as 20 times with the number of city 8, 16, 24 and 32 to see which method is optimal in terms of distance and time computation. Based on experiments conducted with a number of cities 3, 4, 5 and 6 producing the same value and optimal distance for the genetic algorithm and hill climbing, the value of this distance begins to differ with the number of city 7. The overall results shows that these tests, hill climbing are more optimal to number of small cities and the number of cities over 30 optimized using genetic algorithms.
Highlights
Traveling Salesman Problem (TSP) is a complex combinatorial optimization problem, originally presented by Dantzig
Starting from defining the initial group, deciding the better search area up to iterating from level to level, the results of each level is taken from best and compared, so they can get more optimal [7]. This TSP method is used to determine the nodes that has been given the distance among other nodes by comparing the existing node based on selection of the shortest distance from the initial position [8]
Map API that connects coordinate points using the marker of inter-city destinations by salesmen that would be seeing a path to be passed by graph using a polyline, and it will be sorted to obtain the optimal shortest track.The search process using a genetic algorithm for TSP and Hill Climbin
Summary
Traveling Salesman Problem (TSP) is a complex combinatorial optimization problem, originally presented by Dantzig. Starting from defining the initial group, deciding the better search area up to iterating from level to level, the results of each level is taken from best and compared, so they can get more optimal [7]. This TSP method is used to determine the nodes that has been given the distance among other nodes by comparing the existing node based on selection of the shortest distance from the initial position [8]
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