This paper is a survey of genetic algorithms for t h e traveling salesman problem. Genetic algorithms are randomized search techniques that simulate some of the processes observed i n natural evolution. In this paper, a simple genetic algorithm is introduced, and various extensions are presented to solve t h e traveling salesman problem. Computational results are also repor ted for both random ...

This paper presents the application of the PSO (Particle Swarm Optimization) as a tool to solve the Traveling Salesman Problem. The proposed application consists of using a technique based on Artificial Intelligent – AI. It is based in the simulation of social interaction between individuals of a population. Here, each element of population moves in the hyper-space and they are attracted by pos...

The traveling salesman problem (TSP) is a well-known optimization problem in graph theory, as well as in operations research that has nowadays received much attention because of its practical applications in industrial and service problems. In this problem, a salesman starts to move from an arbitrary place called depot and after visits all of the nodes, finally comes back to the depot. The obje...

We introduce a new combinatorial optimization problem, which is a generalization of the Traveling Salesman Problem (TSP) and which we call Traveling Salesman Problem of Second Order (2-TSP). It is motivated by an application in bioinformatics, especially the Permuted Variable Length Markov model. We propose seven elementary heuristics and two exact algorithms for the 2-TSP, some of which are ge...

This paper treats of a generalization of the Traveling Salesman Problem (TSP) called Multi-commodity one-to-one Pickup-and-Delivery Traveling Salesman Problem (m-PDTSP) in which cities corresponds to customers providing or requiring known amounts of m different objects, and the vehicle has a given upper-limit capacity. Each object has exactly one origin and one destination, and the vehicle must...

Imperial competitive algorithm (ICA) simulates a multi-agent algorithm. Each agent is like a kingdom has its country, and the strongest country in each agent is called imperialist, others are colony. Countries are competitive with imperialist which in the same kingdom by evolving. So this country will move in the search space to find better solutions with higher fitness to be a new imperialist....

This paper presents an empirical analysis of some implementations of tour improvement heuristics designed for the pickup and delivery traveling salesman problem. Results show that while the classical 2-opt traveling salesman algorithm can be implemented very efficiently, available implementations of the 3-opt are much less efficient. Among tested algorithms, the only one to produce significant ...

Traveling salesman problems with revenues form a generalization of traveling salesman problems. Here, next to travel costs an explicit revenue is generated by visiting a city. We analyze routing problems with revenues, where a predetermined route on all cities determines the tours along subgroups. Corresponding routing games with revenues are analyzed. It is shown that these games have a nonemp...