A grid-based ant colony algorithm for automatic 3D hose routing

Ant Colony Algorithms applied to difficult combinatorial optimization problems such as the traveling salesman problem (TSP) and the quadratic assignment problem. In this paper we propose a grid-based ant colony algorithm for automatic 3D hose routing. Algorithm uses the tessellated format of the obstacles and the generated hoses in order to detect collisions. The representation of obstacles and hoses in the tessellated format greatly helps the algorithm towards handling free-form objects and speed up the computations. The performance of the algorithm has been tested on a number of 3D models

Hybrid ant colony optimization for grid computing

A hybrid ant colony optimization technique to solve the stagnation problem in grid computing is proposed in this paper.The proposed algorithm combines the techniques from Ant Colony System and Max – Min Ant System and focused on local pheromone trail update and trail limit.The agent concept is also integrated in this proposed technique for the purpose of updating the grid resource table.This facilitates the hybrid ant colony optimization technique in solving the stagnation problem in two ways within one cycle, thus minimize the total computational time of the jobs

Мультиагентный метод с непрямой связью между агентами для выделения информативных признаков

Решена задача отбора информативных признаков. Предложены мультиагентные методы отбора информативных признаков с непрямой связью между агентами на основе представления пунктов назначения признаками и в виде информативности. Проведены эксперименты по решению задачи отбора информативных признаков для моделирования коэффициента упрочнения деталей газотурбинных авиадвигателей после алмазного выглаживания.Вирішено задачу відбору інформативних ознак. Запропоновано мультиагентні методи відбору інформативних ознак з непрямим зв’язком між агентами на основі представлення пунктів призначення ознаками та у вигляді інформативності. Проведено експерименти з вирішення задачі відбору інформативних ознак для моделювання коефіцієнту зміцнення деталей газотурбінних авіадвигунів після алмазного вигладжування.The feature selection problem is solved. Multiagent methods for feature selection with indirect connection between agents are proposed. The experiments to solving of problem of model synthesis of airengine details hardening coefficient are carried out

Ant Colony Optimization. A Computational Intelligence Technique

Ant colony optimization (ACO) is a novel computational technique inspired by a foraging behavior of ants has been successfully applied for solving real world optimization problems. This behavioral pattern inspires artificial ants for the search of solutions to the various types of optimization problems. ACO is a probabilistic search approach founded on the idea of evolutionary process. In this paper, we present an overview of ant colony optimization and ACO variants up to now. we also summarize various types of applications. Finally we focus on some research efforts directed at receiving a dipper understanding of the ant colony optimization algorithms