The problem with TSP is an attempt to find the shortest distance traveled by a salesman in visiting each city without having to visit the same city more than once. The purpose of implementing the I-SOS algorithm in this case is to find the minimum distance traveled, a solution can be obtained after going through the calculation of the mutualism phase, commensalism phase, parasitism phase and predation phase. The resolution of TSP problems in the study begins with the process of identifying each city by providing a random value to represent each destination city. The random value used is between 0 and 1, the random results obtained will then be sorted with the provision that the smallest random value will be used as the initial for city A while the largest random value is used as the initial for city D. In the first random, the random value | 0.5 | 0.27 | 0.75 | 0.25 | the city representation of the random number is | C | B | D | A | or if the values are sorted, the city order will be obtained, namely A = 0.25, B = 0.27, C = 0.5 and D = 0.75, this process will continue until all the organisms defined in the ecosystem are formed
Implementation of Traveling salesman problem Algorithm for Scheduling and Shortest Distance Optimization
