Search results for "Extremal optimization"
showing 2 items of 2 documents
A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics
2006
We propose a new distributed image segmentation algorithm structured as a multiagent system composed of a set of segmentation agents and a coordinator agent. Starting from its own initial image, each segmentation agent performs the iterated conditional modes method, known as ICM, in applications based on Markov random fields, to obtain a sub-optimal segmented image. The coordinator agent diversifies the initial images using the genetic crossover and mutation operators along with the extremal optimization local search. This combination increases the efficiency of our algorithm and ensures its convergence to an optimal segmentation as it is shown through some experimental results.
Strategies for accelerating ant colony optimization algorithms on graphical processing units
2007
Ant colony optimization (ACO) is being used to solve many combinatorial problems. However, existing implementations fail to solve large instances of problems effectively. In this paper we propose two ACO implementations that use graphical processing units to support the needed computation. We also provide experimental results by solving several instances of the well-known orienteering problem to show their features, emphasizing the good properties that make these implementations extremely competitive versus parallel approaches.