The channel-assignment problem (CAP) in cellular radio networks is known to belong to the class of NPcomplete optimization problems. Many heuristic techniques including Hopfield neural networks (HNN) have been devised for solving the CAP. However, HNNs often suffer from local minima. On the other hand, a recently proposed transiently chaotic neural network (TCNN) has been successfully used in s...

In traditional Genetic Algorithm, random population seeding technique is simple and efficient however the population may contain poor quality individuals which take long time to converge optimal solution. This motivates to design a population initialization technique with the features of randomness, individual diversity and good quality. In this paper, an initial work has been carried out to de...

The multiple traveling salesman problem (MTSP) is a generalization of the famous traveling salesman problem (TSP), where more than one salesman is used in the solution. Although the MTSP is a typical kind of computationally complex combinatorial optimization problem, it can be extended to a wide variety of routing problems. This paper presents an efficient and evolutionary optimization algorith...

The k-traveling salesman problem, or k-TSP is: given a graph with edge weights and an integer k, find a simple cycle of minimum weight visiting exactly k nodes. To obtain lower bounds for the traveling salesman problem the 2-matching relaxation and the 1-tree relaxation can be used. We generalize these two relaxations for the k-TSP.

The probabilistic travelling salesman problem (PTSP) is an extension of the well-known travelling salesman problem (TSP), which has been extensively studied in the field of combinatorial optimization. The goal of the TSP is to find the minimum length of a tour to all customers, given the distances between all pairs of customers whereas the objective of the PTSP is to minimize the expected lengt...

Swarm intelligence is the technological modeling of behaviors of social insects, such as the ant or the honeybee. Although each element comprising swarm intelligence is simple, high grade intelligence emerges when the elements gather to form a swarm. Ant Colony Optimization (Dorigo, M, et al., 1997), which is called ACO, is one of the swarm intelligence and has been attracting much attention re...

The standard Genetic Algorithm often suffers from slow convergence for solving combinatorial optimization problems. In this study, we present a sequence based genetic algorithm (SBGA) for the symmetric travelling salesman problem (TSP). In our proposed method, a set of sequences are extracted from the best individuals, which are used to guide the search of SBGA. Additionally, some procedures ar...

Ant Colony System (ACS) is a distributed (agentbased) algorithm which has been widely studied on the Symmetric Travelling Salesman Problem (TSP). The optimum parameters for this algorithm have to be found by trial and error. We use a Particle Swarm Optimization algorithm (PSO) to optimize the ACS parameters working in a designed subset of TSP instances. First goal is to perform the hybrid PSO-A...

Davis presented the order crossover operator for solving the travelling salesman problem (TSP) using genetic algorithm and has described two basic variants of this order crossover operator. In order to improve the efficiency and validity of these variants, in this paper three new variations of the order crossover operator are presented. These are programmed in C++ and implemented on a set of be...