Question

compare between Genetic Algorithms ( GA) and Particle Swarm Optimization (PSO) algorithms to solve Travelling Salesman Problem (TSP): find shortest path to visit 26 cities. write java code for both , then run the to compare between them in terms of time complexcity and optimality (show the optimal path found by each algorithm).

Answer 1

The traveling salesman problem (TSP) is a well-known and important combinatorial optimization problem. Generally, the process is as follows: start by choosing any city in a given list and end up by returning to the departure one. The traveled distance must be minimized knowing that the distances between cities are known. The notion of distance may be replaced by the time or the cost. According to Kemighan [12], the definition of the traveling salesman problem is as following: Given a graph G = (N, A), where N = {v0, v1….. vn} is the set of nodes (cities). And let A = {(vi, vj) / vi, vj Є N, i <j} be the set of stops that connect the nodes if the distances are symmetrical and A = {(vi, vj ) / vi, vj Є N i ≠ j} represents the arcs if the distances are asymmetric. In other words, the problem is symmetrical if the distance for the trip from town A to town B is the same as the reverse on