This paper presents a heuristic technique that uses the Wang Recurrent Neural Network with the "Winner Takes All" principle to solve the Traveling Salesman Problem. When the Wang Neural Network presents solutions for the Assignment Problem with all constraints satisfied, the "Winner Takes All" principle is applied to the values in the Neural Network’s decision variables, with the additional con...

The traveling salesman problem is one of the most famous combinatorial problems. We identify a natural parameter for the two-dimensional Euclidean traveling salesman problem. We show that for random problems there is a rapid transition between soluble and insoluble instances of the decision problem at a critical value of this parameter. Hard instances of the traveling salesman problem are assoc...

OF THESIS GENERALIZED PARTITION CROSSOVER FOR THE TRAVELING SALESMAN

Traveling salesman problem is of the known and classical problems at Research in Operations. Many scientific activities can be solved as traveling salesman problem. Existing methods for solving hard problems (such as the traveling salesman problem) consists of a large number of variables and constraints which reduces their practical efficiency in solving problems with the original size. In rece...

Multiple Traveling Salesman Problem (MTSP) is an important combinatorial optimization problem. However, it is applicable to only the cases in which multiple executing individuals (traveling salesman) share the common workspace (city set). It cannot be used to handle many multi-machine engineering systems where multiple machines’ workspaces are not the same and partially overlap with each other....

The double traveling salesman problem with multiple stacks is a variant of the pickup and delivery traveling salesman problem in which all pickups must be completed before any of the deliveries. In addition, items can be loaded on multiple stacks in the vehicle and each stack must obey the last-in-first-out policy. The problem consists in finding the shortest Hamiltonian cycles covering all pic...