Multiple Objective TSP based on ACO
نویسندگان
چکیده
In this paper we present an Ant Colony Optimisation based algorithm to determine the Pareto set for the Multiple Objective Travelling Salesman Problem. Our results are then compared with the ones obtained with a genetic algorithm.
منابع مشابه
HYBRID ARTIFICIAL NEURAL NETWORKS BASED ON ACO-RPROP FOR GENERATING MULTIPLE SPECTRUM-COMPATIBLE ARTIFICIAL EARTHQUAKE RECORDS FOR SPECIFIED SITE GEOLOGY
The main objective of this paper is to use ant optimized neural networks to generate artificial earthquake records. In this regard, training accelerograms selected according to the site geology of recorder station and Wavelet Packet Transform (WPT) used to decompose these records. Then Artificial Neural Networks (ANN) optimized with Ant Colony Optimization and resilient Backpropagation algorith...
متن کاملResearch on Traveling Salesman Problem Based on the Ant Colony Opti- mization Algorithm and Genetic Algorithm
In this paper, we prompt a new multi-dimensional algoithm to solve the traveling salesman problem based on the ant colony optimization algorithm and genetic algorithm. Ant Colony Optimization (ACO) is a heuristic algorithm which has been proven a successful technique and applied to a number of combinatorial optimization (CO) problems. The traveling salesman problem (TSP) is one of the most impo...
متن کاملA memetic ant colony optimization algorithm for the dynamic travelling salesman problem
Ant colony optimization (ACO) has been successfully applied for combinatorial optimization problems, e.g., the travelling salesman problem (TSP), under stationary environments. In this paper, we consider the dynamic TSP (DTSP), where cities are replaced by new ones during the execution of the algorithm. Under such environments, traditional ACO algorithms face a serious challenge: once they conv...
متن کاملA statistical analysis of parameter values for the rank-based ant colony optimization algorithm for the traveling salesperson problem
Ant colony optimization (ACO) is a metaheuristic for solving combinatorial optimization problems that is based on the foraging behavior of biological ant colonies. Starting with the 1996 seminal paper by Dorigo, Maniezzo and Colorni, ACO techniques have been used to solve the traveling salesperson problem (TSP). In this paper, we focus on a particular type of the ACO algorithm, namely, the rank...
متن کاملAn Analysis of Algorithmic Components for Multiobjective Ant Colony Optimization: A Case Study on the Biobjective TSP
In many practical problems, several conflicting criteria exist for evaluating solutions. In recent years, strong research efforts have been made to develop efficient algorithmic techniques for tackling such multi-objective optimization problems. Many of these algorithms are extensions of well-known metaheuristics. In particular, over the last few years, several extensions of ant colony optimiza...
متن کامل