Jumping PSO with Expanding Neighborhood Search for TSP on a Cuboid

Path planning on the surfaces of a cuboidshaped object is a scientific value and practical significance of the research topic, because of its potential applications with many fields. On basis of analysis for calculation of the minimum distance of any two points on a cuboid, by incorporating Expanding neighborhood search (ENS) procedure into the algorithm, a new discrete jumping particle swarm algorithm, ENS-JPSO, is presented for solving the traveling salesman problems on the surfaces of a cuboid, in which the path-relinking strategy is used to update velocities and positions of particles in the swarm, in order to improve the exploitation capability of the algorithm. After visual implementation of the experimental system in Java with 3D APIs, The effectiveness of the proposed method are tested on several TSPLIB instances with satisfactory results. And further comparison with other methods for various sets of random points has demonstrated that the proposed algorithm is able to obtain the best route for large-scale instances of TSPs on a cuboid.