Model Checking is a technique for automatically checking the model representing software or hardware about whether they satisfy the corresponding specifications. Traditionally, the model checking uses deterministic algorithms, but the deterministic algorithms have a fatal problem. They are consuming too many computer resources. In order to mitigate the problem, an approach based on the Ant Colo...

BACKGROUND The accountable care organization (ACO) is a new organizational form to manage patients across the continuum of care. There are numerous questions about how ACOs should be optimally structured, including compensation arrangements with primary care physicians. METHODS Using data from a national survey of physician practices, we compared primary care physicians' compensation between ...

The population-based ant colony optimization algorithm (PACO) uses a very different pheromone update when compared to other ACO algorithms. In this work, we study P-ACO’s behavior for solving the traveling salesman problem (TSP) and the quadratic assignment problem (QAP). In particular, we investigate the impact of a local search on P-ACO parameters and performance. The results clearly show tha...

Intrusion detection is a problem of great significance to protecting information systems security. An intruder may move between multiple nodes in the network to conceal the origin of attack. Distributed intrusion detection and prevention plays an increasingly important role in securing computer networks. To overcome the limitations of conventional intrusion detection systems, alerts are made in...

Swarm Intelligence (SI) is a relatively new technology that takes its inspiration from the behavior of social insects and flocking animals. In this paper, we focus on two main SI algorithms: Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). An extension of ACO algorithm and a PSO algorithm has been implemented to solve the portfolio optimization problem, which is a continuous...

Ant Colony Optimisation (ACO) is a constructive metaheuristic that uses an analogue of ant trail pheromones to learn about good features of solutions. ACO implementations are typically tailored in an ad hoc manner to suit particular problems. Critically, the pheromone representation for a particular problem is usually chosen intuitively rather than by following any systematic process. In some r...

A system based on the adaptation of the search principle used in ant colony optimization (ACO) for multiobjective graph-based data mining (GBDM) is introduced in this paper. Our multiobjective ACO algorithm is designed to retrieve the best substructures in a graph database by jointly considering two criteria, support and complexity. The experimental comparison performed with a classical GBDM me...