Search results for "ALGORITHMS"
showing 10 items of 1716 documents
A general framework for a class of non-linear approximations with applications to image restoration
2018
Este artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://www.sciencedirect.com/science/article/abs/pii/S0377042717301188 Este es el pre-print del siguiente artículo: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applications to image restoration. Journal of Computational and Applied Mathematics, vol. 330 (mar.), pp. 982-994, que se ha publicado de forma definitiva en https://doi.org/10.1016/j.cam.2017.03.008 This is the pre-peer reviewed version of the following article: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applic…
A fast heuristic for solving the D1EC coloring problem
2010
In this paper we propose an efficient heuristic for solving the Distance-1 Edge Coloring problem (D1EC) for the on-the-fly assignment of orthogonal wireless channels in wireless as soon as a topology change occurs. The coloring algorithm exploits the simulated annealing paradigm, i.e., a generalization of Monte Carlo methods for solving combinatorial problems. We show that the simulated annealing-based coloring converges fast to a sub optimal coloring scheme even for the case of dynamic channel allocation. However, a stateful implementation of the D1EC scheme is needed in order to speed-up the network coloring upon topology changes. In fact, a stateful D1EC reduces the algorithm’s convergen…
Towards Multilevel Ant Colony Optimisation for the Euclidean Symmetric Traveling Salesman Problem
2015
Ant Colony Optimization ACO metaheuristic is one of the best known examples of swarm intelligence systems in which researchers study the foraging behavior of bees, ants and other social insects in order to solve combinatorial optimization problems. In this paper, a multilevel Ant Colony Optimization MLV-ACO for solving the traveling salesman problem is proposed, by using a multilevel process operating in a coarse-to-fine strategy. This strategy involves recursive coarsening to create a hierarchy of increasingly smaller and coarser versions of the original problem. The heart of the approach is grouping the variables that are part of the problem into clusters, which is repeated until the size…
A challenging family of automata for classical minimization algorithms
2010
In this paper a particular family of deterministic automata that was built to reach the worst case complexity of Hopcroft's state minimization algorithm is considered. This family is also challenging for the two other classical minimization algorithms: it achieves the worst case for Moore's algorithm, as a consequence of a result by Berstel et al., and is of at least quadratic complexity for Brzozowski's solution, which is our main contribution. It therefore constitutes an interesting family, which can be useful to measure the efficiency of implementations of well-known or new minimization algorithms.
α-stable distributions for better performance of ACO in detecting damage on not well spaced frequency systems
2014
Abstract In this paper, the Ant Colony Optimization (ACO) algorithm is modified through α -stable Levy variables and applied to the identification of incipient damage in structural components. The main feature of the proposed optimization is an improved ability, which derives from the heavy tails of the stable random variable, to escape from local minima. This aspect is relevant since the objective function used for damage detection may have many local minima which render very challenging the search of the global minimum corresponding to the damage parameter. As the optimization is performed on the structural response and does not require the extraction of modal components, the method is pa…
A simulation/optimization model for selecting infrastructure alternatives in complex water resource systems
2010
The paper introduces a simulation/optimization procedure for the assessment and the selection of infrastructure alternatives in a complex water resources system, i.e. in a multisource (reservoirs) multipurpose bulk water supply scheme. An infrastucture alternative is here a vector X of n decision variables describing the candidate expansions/new plants/water transfers etc. Each parameter may take on a discrete number of values, with its own investment cost attached. The procedure uses genetic algorithms for the search of the optimal vector X through operators mimicking the mechanisms of natural selection. For each X, the value of the objective function (O.F.) is assessed via a simulation mo…
Improving Performance of Evolutionary Algorithms with Application to Fuzzy Control of Truck Backer-Upper System
2013
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2013/709027 Open access We propose a method to improve the performance of evolutionary algorithms (EA). The proposed approach defines operators which can modify the performance of EA, including Levy distribution function as a strategy parameters adaptation, calculating mean point for finding proper region of breeding offspring, and shifting strategy parameters to change the sequence of these parameters. Thereafter, a set of benchmark cost functions is utilized to compare the results of the proposed method with some other well-known algorithms.…
On Randomness and Structure in Euclidean TSP Instances: A Study With Heuristic Methods
2021
Prediction of the quality of the result provided by a specific solving method is an important factor when choosing how to solve a given problem. The more accurate the prediction, the more appropriate the decision on what to choose when several solving applications are available. In this article, we study the impact of the structure of a Traveling Salesman Problem instance on the quality of the solution when using two representative heuristics: the population-based Ant Colony Optimization (ACO) and the local search Lin-Kernighan (LK) algorithm. The quality of the result for a solving method is measured by the computation accuracy, which is expressed using the percent error between its soluti…
A tabu search algorithm for large-scale guillotine (un)constrained two-dimensional cutting problems
2002
Abstract In this paper we develop several heuristic algorithms for the two-dimensional cutting problem (TDC) in which a single stock sheet has to be cut into a set of small pieces, while maximising the value of the pieces cut. They can be considered to be general purpose algorithms because they solve the four versions of the TDC: weighted and unweighted, constrained and unconstrained. We begin by proposing two constructive procedures based on simple bounds obtained by solving one-dimensional knapsack problems. We then use these constructive algorithms as building blocks for more complex procedures. We have developed a greedy randomised adaptive search procedure (GRASP) which is very fast an…
On the approximability of the range assignment problem on radio networks in presence of selfish agents
2005
AbstractWe consider the range assignment problem in ad-hoc wireless networks in the context of selfish agents: A network manager aims to assigning transmission ranges to the stations in order to achieve strong connectivity of the network within a minimal overall power consumption. Station is not directly controlled by the manager and may refuse to transmit with a certain transmission range because it might be costly in terms of power consumption.We investigate the existence of payment schemes which induce the stations to follow the decisions of a network manager in computing a range assignment, that is, truthful mechanisms for the range assignment problem. We provide both positive and negat…