The crowding population based ant colony optimization algorithm (CP-ACO) uses a different pheromone update in comparison to other ACO algorithms. In this paper, crowding population based ant colony optimization algorithm is proposed to solve service restoration problem. The most notable achievement featured in this paper is run time reduction of algorithm to solve the service restoration task. ...

With the speeding up of urbanization in our country, the situation of urban emergency is getting more and more serious; therefore, it is necessary to promote the study in urban emergency management, so as to enhance the city ability of resisting the emergency. Based on the defects of the emergency vehicle routing choosing, the paper puts forward a particle swarm optimization based ant colony al...

Intruders often combine exploits against multiple vulnerabilities in order to break into the system. Each attack scenario is a sequence of exploits launched by an intruder that leads to an undesirable state such as access to a database, service disruption, etc. The collection of possible attack scenarios in a computer network can be represented by a directed graph, called network attack gra...

Ant colony optimization is an ant algorithm framework that took inspiration from foraging behavior of ant colonies. Indeed, ACO algorithms use a chemical communication, represented by pheromone trails, to build good solutions. However, ants involve different communication channels to interact. Thus, this paper introduces the acoustic communication between ants while they are foraging. This proc...

The DBSCALE [1] algorithm is a popular algorithm in Data Mining field as it has the ability to mine the noiseless arbitrary shape Clusters in an elegant way. Such metaheuristic algorithms include Ant Colony Optimization Algorithms, Particle Swarm Optimizations and Genetic Algorithm has received increasing attention in recent years. Ant Colony Optimization (ACO) is a technique that was introduce...

Aiming to the demand and characteristics of vehicle scheduling optimization problem in emergency rescue, this paper establishes a multi-objective optimization model, which takes minimizing variable bidirectional distance, path risk and cost as the optimization target. To avoid the prematurely falling into local optimization of ant colony system(ACS)algorithm, and to improve the algorithm adapta...

Segmentation is one of the essential tasks in image processing. Thresholding is one of the simplest techniques for performing image segmentation. Multilevel thresholding is a simple and effective technique. The primary objective of bi-level or multilevel thresholding for image segmentation is to determine a best thresholding value. To achieve multilevel thresholding various techniques has been ...

Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for attacking hard combinatorial optimization problems. Yet, its performance, when compared to more fine-tuned algorithms, was rather poor for large instances of traditional benchmark problems like the Traveling Salesman Problem. To show that Ant Colony Optimization algorithms could be good alternatives to exi...

Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for attacking hard combinatorial optimization problems. Yet, its performance, when compared to more fine-tuned algorithms, was rather poor for large instances of traditional benchmark problems like the Traveling Salesman Problem. To show that Ant Colony Optimization algorithms could be good alternatives to exi...

Ant Colony Optimization is a probabilistic technique for finding the optimal path for reaching a destination using graphs. This algorithm was further developed to introduce the concept of Multiple Ant Colony Optimization technique in which ants were classified into various families that worked to provide optimal path solutions to the destination for their own family. This paper aims at proposin...