Search results for "Ant colony optimization algorithms"
showing 9 items of 29 documents
Multiobjective ant colony search algorithm optimal electrical distribution system planning
2005
A dynamic multiobjective, MO, algorithm based on the ant colony search, the multiobjective ant colony search algorithm, MOACS, is presented. The application domain is that of dynamic planning for electrical distribution systems. A time horizon of H years has been considered during which the distribution system are modified according to the new internal (loads) and external (market, reliability, power quality) requirements. In this scenario, the objectives the Authors consider most important for utilities in strategical planning are: the quality requirement connected to the decrease of the expected number of interruptions per year and customer, in the considered time frame, and the choice fo…
Integrated Production and Predictive Maintenance Planning based on Prognostic Information
2019
International audience; This paper address the problem of scheduling production and maintenance operation in predictive maintenance context. It proposes a contribution in the decision making phase of the prognostic and health management framework. Theprognostics and decision processes are merged and an ant colony optimization approach for finding the sequence of decisions that optimizes the benefits of a production system is developed. A case study on a single machine composed of several components where machine can have several usage profiles. The results show thatour approach surpasses classical condition based maintenance policy.
On the Use of Prognostics and Health Management to Jointly Schedule Production and Maintenance on a Single Multi-purpose Machine
2020
This paper address the problem of using prognostic information in the decision-making process of a single multi-purpose machine. The prognostics and health management method is compared to condition-based maintenance combined with a genetic algorithm to determine the joint schedule of maintenance and production. The paper presents a methodology to select the adequate strategy while considering several factors that influence the functioning of the machine. The results show that operational and conditions variability influence the choice of the suitable methods. In the presented case, we show configurations where prognostic information is useless or useful.
Composite laminates buckling optimization through Levy based Ant Colony Optimization
2010
In this paper, the authors propose the use of the Levy probability distribution as leading mechanism for solutions differentiation in an efficient and bio-inspired optimization algorithm, ant colony optimization in continuous domains, ACOR. In the classical ACOR, new solutions are constructed starting from one solution, selected from an archive, where Gaussian distribution is used for parameter diversification. In the proposed approach, the Levy probability distributions are properly introduced in the solution construction step, in order to couple the ACOR algorithm with the exploration properties of the Levy distribution. The proposed approach has been tested on mathematical test functions…
Training label cleaning with ant colony optimization for classification of remote sensing imagery
2015
This paper presents an original approach for improving performances of the supervised classifiers in remote sensing imagery by proposing a technique to refine a given training set using Ant Colony Optimization (ACO). The new method called ACO-Training Label Cleaning (ACO-TLC) applies ACO model for selection of the significant training samples from a given set of labeled vectors in order to optimize the quality of a supervised classifier. This means to retain the most informative samples and to remove the uncertain or misclassified training samples, which lead to classification errors. As a result of the selection process, we can obtain a purified training set. The proposed model is implemen…
A grid ant colony algorithm for the orienteering problem
2005
In this paper we propose a distributed ant colony algorithm to solve large scale orienteering problem instances. Our approach is based on a multi-colony strategy where each colony works in an independent portion (cluster) in the original graph. This results in no need for communicating pheromones information among colonies and in increasing speedup. We have implemented our algorithm as a .NET Web services infrastructure following a grid computing philosophy and we provide some promising experimental results to show the feasibility and effectiveness of our approach
A novel identification method for generalized T-S fuzzy systems
2012
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/893807 In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm
Drivers-Inspired Ants for Solving the Vehicle Routing Problem with Time Windows
2016
International audience; In our study, we develop a method that merges two information sources within ants colony optimization heuristic. Namely artificial ants which occurs for short term optimization and transporter's vehicles that occurs in long term and continuous optimization toward solving the real-world vehicle routing problem. This study is supported by a transporter (Upsilon) of the region of l'Yonne in France and a transport and logistics software development company (Tedies). Our method suits for transporters that use human planners to make decisions about their tours and intending to move to computer planners without drastically upsetting the drivers habits. Hence, the pledge of …
Damage identification by Lévy ant colony optimization
2010
This paper deals with the identification of incipient damage in structural elements by non-destructive test based on experimentally measured structural dynamical response. By applycation of the Hilbert transform to the recorded signal the so-called phase of the analytical signal is recovered and a proper functional is constructed in such a way that its global minimum gives a measure of the damage level, meant as stiffness reduction. Minimization is achieved by applying a modified Ant Colony Optimization (ACO) for continuous variables, inspired by the ants’ forageing behavior. The modification consists in the application of a new perturbation operator, based on alpha stable Lévy distribution…