The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper proposes a hybrid Harmony Search algorithm for the bin-packing problem. The bin-packing problem is a well-known NP-Hard optimization problem. The proposed algorithm (called BPHS) combines a harmony search algorithm, that employs a tournament selection in the generation of new candidate solutions, with a variable neighbourhood search to improve the exploitation ability of the algorithm....
There are several factors that can influence the selection of electives in order to complete the set of credits of a course in Bachelor level. Even though this problem has been studied repeatedly by many researchers on literature, the results have not established optimal values using bio-inspired algorithms to analyze the cost-benefit for every student in a minority group, and comparing their choices...
In this paper, we present an image segmentation technique based on fuzzy c-means (FCM) incorporated with wavelet domain noise filtration. With the use of image noise feature estimation composed of preliminary coefficient classification and wavelet domain indicator, a filter for balancing the preservation of relevant details against the degree of noise reduction can be created. The filter is further...
Multi-objective optimization inspired on genetic algorithms are population based search methods. The population elements, chromosomes, evolve using inheritance, mutation, selection and crossover mechanisms. The aim of these algorithms is to obtain a representative non-dominated Pareto front from a given problem. Several approaches to study the convergence and performance of algorithm variants have...
A major challenge in DNA computing area is to design autonomous and programmable biomolecular devices built on DNA. The significant achievement in the field of DNA nanodevices was a laboratory implementation of the 2-state biomolecular finite automaton based on one restriction enzyme FokI [3]. Although this practical implementation represents a proof of concept for autonomous computing with DNA molecules,...
In this paper, we optimize the Reporting Cells Planning Problem in a realistic mobile network. To the best of our knowledge, this is the first work in the literature in which the Reporting Cells Planning Problem is studied in a realistic mobile environment. This problem is based on a mobile location management strategy where the network cells can be in two possible states: Reporting Cells and non-Reporting...
The inference of phylogenetic relationships represents one of the most challenging problems in bioinformatics. The increasing availability of biological data motivates the development of new algorithmic designs to conduct phylogenetic analyses on exponentially increasing search spaces. Bioinspired metaheuristics have arisen as a useful approach to address this problem, introducing different search...
A three-dimensional CA model for the simulation of Portland cement microstructure development has been developed in this paper. The Gene Expression Programming (GEP) algorithm is employed as the learning algorithm to evolve the transition rule reversely from the microstructure development characteristic data due to hydration reactions. The characteristic data is extracted from 8-bit gray images that...
Floating Centroids Method (FCM) is a new method to improve the performance of neural network classifier. But the K-Means clustering algorithm used in FCM is sensitive to outliers. So this weakness will influence the performance of classifier to a certain extent. In this paper, K-Medoids clustering algorithm which can diminish the sensitivity to the outliers is used to partition the mapping points...
In dynamic environment, Learning Classifier System (LCS) evolves classifiers to fit the current situation, but may forget classifiers which were useful for previous situations. Our main idea is that, we store the forgotten classifiers as archives and generate new classifiers by recombining them to fit the current situation. Specifically, we propose an archive-based LCS called Arc-XCS, which detects...
Magnetotactic bacteria optimization algorithm (MBOA) is a kind of optimization algorithm inspired by the characteristics of magnetotactic bacteria(MTB). They have chains consisting of micro magnetic particles called magnetosomes inside their bodies. These magnetic chains make MTB have magnetotaxis that make them orient and swim along geomagnetic field lines. The original MBOA mimics the interaction...
For many decades neuroscience researchers have been interested in harnessing the computational power of the mammalian nervous system. However, the vast complexity of such a nervous system has made it very difficult to fully understand basic functions such as movement, touch and learning. More recently the nervous system of the C. elegans nematode has been widely studied and there now exists a vast...
In the current global market organizations face uncertainties and shorter response time. In order to remain competitive many organizations adopted flexible resources capable of performing several operations with different performance capabilities. The unrelated parallel-machines makespan minimization problem (Rm∥Cmax) is known to be NP-hard or too complex to be solved exactly. Among the several heuristics...
This paper presents a programable perturbation and observation control implementation for a wind generation system and its power electronic converter. The objective of the method in this particular application is to adjust the power delivered to charge a battery to its maximum and allowable value, function of the real values of several parameters and their continuous variation, the most important...
Genetic programming (GP) has been applied to solve data classification problems numerous times in previous studies and the findings in the literature confirm that GP is able to perform well. In more recent studies, researchers have shown that using a team of classifiers can outperform a single classifier. These teams are referred to as ensembles. Previously, several different attempts at creating...
We demonstrate how Residual-Based Fault Detection can be improved by means of Genetic-Fuzzy Systems (GFSs). Thus, the performance of a pure Data-Driven Fault Detection System, which relies on system identification models, is improved using models created by Genetic-Fuzzy Systems. The evolutionary approach is used in the cases where a deterministic training of the fuzzy systems is not able to produce...
Extended Manufacturing Environments (EMEs) are nowadays growing due to the increase on Distributed and Virtual Enterprises, which led to an emergent need to apply scheduling approaches accordingly. This can be achieved in several different ways, namely by putting forward new approaches or by trying to adapt existing ones. In this paper the adaptation of some existing scheduling methods is proposed...
User modeling and user adaptive interaction research areas are becoming crucial applied issues to understand and support users as they interact with technology. Modeling the decisions to be made and the constraints placed by market globalization in a way that can address the needs of all stakeholders has been a long time area of academic and industrial research, mainly for Planning, Scheduling, and...
A fuzzy linguistic controller has been developed and implemented with the aim to cope with interactions between control loops due to coupling effects. To access the performance of the proposed approach several experiments have also been conducted using the classical PID controllers in the control loops. A mixing process has been used as test bed of all controllers experimented and the corresponding...
The paper presents a study about optimal supply of the energy service, using simulations of network operation scenarios, in order to optimize resources and minimize the variables: operation cost, energy losses, generation cost and consumers shedding. These simulations create optimal operation models of the network, allowing the system operator obtain knowledge to take pre-established procedures that...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.