ABSTRACT
The paper presents a study of the effectiveness of the multithreading implementation of an ant colony optimization algorithm for solving the traffic flow estimation problem. A model of the problem, using graph of the city map, and mathematical formulation of the algorithm, using simulated ants, are described. Experimental results from comparison of the sequential and the multithreading implementation of the algorithm with varying number of graph nodes and ants are summarized.
- Bolufé-Röhler, A., J. Pereira, S. Fiol-González. Traffic Flow Estimation Using Ant Colony Optimization Algorithms. Computación y Sistemas 18.1, 2014.Google Scholar
- Di Caro, G., M. Dorigo. AntNet: Distributed stigmergetic control for communications networks. Journal of Artificial Intelligence Research, pp. 317--365, 1998. Google ScholarDigital Library
- Dorigo, M., G. Caro. Ant colony optimization: a new meta-heuristic. Evolutionary Computation. CEC 99. Proceedings of the 1999 Congress on. Vol. 2. IEEE, 1999.Google Scholar
- Dorigo, M., G. Caro, L. Gambardella. Ant algorithms for discrete optimization. Artificial life 5.2: 137--172, 1999. Google ScholarDigital Library
- Haldenbilen, S., O. Baskan, C. Ozan. An Ant Colony Optimization Algorithm for Area Traffic Control. Ant Colony Optimization-Techniques and Applications. InTech, 2013.Google ScholarCross Ref
- Sawadogo, M., D. Anciaux. Sustainable supply chain by intermodal itinerary planning: a multiobjective ant colony approach, 2012.Google Scholar
- Walkowiak, K. Ant algorithm for flow assignment in connection-oriented networks, 2005.Google Scholar
- Wardrop, J. ROAD PAPER. SOME THEORETICAL ASPECTS OF ROAD TRAFFIC RESEARCH. Proceedings of the institution of civil engineers 1.3. pp. 325--362, 1952.Google Scholar
Recommendations
Memcomputing Implementation of Ant Colony Optimization
We report on similarities between memcomputing with memristive networks and ant colony optimization. In particular, we show that one can design memristive networks to solve short-path optimization problems in a way similar to that done by ant-colony ...
A new solution algorithm for improving performance of ant colony optimization
This study proposes an improved solution algorithm using ant colony optimization (ACO) for finding global optimum for any given test functions. The procedure of the ACO algorithms simulates the decision-making processes of ant colonies as they forage ...
An augmented Lagrangian ant colony based method for constrained optimization
One of the most efficient penalty based methods to solve constrained optimization problems is the augmented Lagrangian algorithm. This paper presents a constrained optimization algorithm to solve continuous constrained global optimization problems. The ...
Comments