Heterogeneity in learning groups is said to improve academic performance. But only few collaborative online systems consider the formation of heterogeneous groups. In this paper we propose a mathematical approach to form heterogeneous groups based on personality traits and the performance of students. We also present a tool that implements this mathematical approach, using an Ant Colony Optimiz...

In this paper we consider MAX–MIN Ant System and Ant Colony System. They are generally recognized to be the best performing algorithms of the Ant Colony Optimization family. They are characterized by a quite different way for dealing with the pheromone trail. We propose an experimental analysis for observing whether this difference impacts significantly on the characteristics of the pheromone d...

In this paper an Ant Colony Optimization (ACO) approach is extended to the safety and time critical domain of air traffic management. This approach is used to generate a set of safe weather avoidance trajectories in a high fidelity air traffic simulation environment. Safety constraints are managed through an enumeration-and-elimination procedure. In this procedure the search space is discretize...

Earthquakes frequently destroy the homes and livelihoods of thousands. One of the most important concerns after an earthquake is to find a safe shelter for the affected people. Because of large numbers of potential locations, the multitude of constraints (e.g. access to infrastructures; security); and the uncertainty prevailing (e.g., number of places required) the identification of optimal she...

We propose a Grammatical Evolution approach to the automatic design of Ant Colony Optimization algorithms. The grammar adopted by this framework has the ability to guide the learning of novel architectures, by rearranging components regularly found on human designed variants. Results obtained with several TSP instances show that the evolved algorithmic strategies are effective, exhibit a good g...

(2008) Flexible protein folding by ant colony optimization.

Article history: Received 2 March 2014 Received in revised form 13 May 2014 Accepted 28 May 2014 Available online 23 June 2014

In this paper, an effective ant colony algorithm is proposed for solving the graph planarization problem. In the proposed algorithm, two kinds of pheromone are adopted to reinforce the search ability, and each kind of pheromone consists of two elements. The proposed algorithm is verified by a large number of simulation runs and compared with other algorithms. The experiment results show that th...

In this contribution, we will study the influence of the three components of the Best-Worst Ant System (BWAS) algorithm. As the importance of each of them as the fact whether all of them are necessary will be analyzed. Besides, we will introduce a new algorithm called BestWorst Ant Colony System by combining the basis of the Ant Colony System with the special components of the BWAS. The perform...