Boosting the performance of metaheuristics for the MinLA problem using a more discriminating evaluation function

International audience

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

A physical packing sequence algorithm for the container loading problem with static mechanical equilibrium conditions

The container loading problem (CLP) is a combinatorial optimization problem for the spatial arrangement of cargo inside containers so as to maximize the usage of space. The algorithms for this problem are of limited practical applicability if real-world constraints are not considered, one of the most important of which is deemed to be stability. This paper addresses static stability, as opposed to dynamic stability, looking at the stability of the cargo during container loading. This paper proposes two algorithms. The first is a static stability algorithm based on static mechanical equilibrium conditions that can be used as a stability evaluation function embedded in CLP algorithms (e.g. constructive heuristics, metaheuristics). The second proposed algorithm is a physical packing sequence algorithm that, given a container loading arrangement, generates the actual sequence by which each box is placed inside the container, considering static stability and loading operation efficiency constraints.

Natural Object Categorization

This thesis addresses the problem of categorizing natural objects. To provide a criteria for categorization we propose that the purpose of a categorization is to support the inference of unobserved properties of objects from the observed properties. Because no such set of categories can be constructed in an arbitrary world, we present the Principle of Natural Modes as a claim about the structure of the world. We first define an evaluation function that measures how well a set of categories supports the inference goals of the observer. Entropy measures for property uncertainty and category uncertainty are combined through a free parameter that reflects the goals of the observer. Natural categorizations are shown to be those that are stable with respect to this free parameter. The evaluation function is tested in the domain of leaves and is found to be sensitive to the structure of the natural categories corresponding to the different species. We next develop a categorization paradigm that utilizes the categorization evaluation function in recovering natural categories. A statistical hypothesis generation algorithm is presented that is shown to be an effective categorization procedure. Examples drawn from several natural domains are presented, including data known to be a difficult test case for numerical categorization techniques. We next extend the categorization paradigm such that multiple levels of natural categories are recovered; by means of recursively invoking the categorization procedure both the genera and species are recovered in a population of anaerobic bacteria. Finally, a method is presented for evaluating the utility of features in recovering natural categories. This method also provides a mechanism for determining which features are constrained by the different processes present in a multiple modal world.

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

Avaliação estatística de métodos de poda aplicados em neurônios intermediários da rede neural MLP

There are several papers on pruning methods in the artificial neural networks area. However, with rare exceptions, none of them presents an appropriate statistical evaluation of such methods. In this article, we proved statistically the ability of some methods to reduce the number of neurons of the hidden layer of a multilayer perceptron neural network (MLP), and to maintain the same landing of classification error of the initial net. They are evaluated seven pruning methods. The experimental investigation was accomplished on five groups of generated data and in two groups of real data. Three variables were accompanied in the study: apparent classification error rate in the test group (REA); number of hidden neurons, obtained after the application of the pruning method; and number of training/retraining epochs, to evaluate the computational effort. The non-parametric Friedman's test was used to do the statistical analysis.

Geração e otimização de trajetórias de um manipulador robótico utilizando algoritmos genéticos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Towards the automatic generation of card games through Grammar-Guided Genetic Programming

We demonstrate generating complete and playable card games using evolutionary algorithms. Card games are represented in a previously devised card game description language, a context-free grammar. The syntax of this language allows us to use grammar-guided genetic programming. Candidate card games are evaluated through a cascading evaluation function, a multi-step process where games with undesired properties are progressively weeded out. Three representa- tive examples of generated games are analysed. We observed that these games are reasonably balanced and have skill ele- ments, they are not yet entertaining for human players. The particular shortcomings of the examples are discussed in re- gard to the generative process to be able to generate quality games

Building and applying a concept hierarchy representation of a user profile

Term dependence is a natural consequence of language use. Its successful representation has been a long standing goal for Information Retrieval research. We present a methodology for the construction of a concept hierarchy that takes into account the three basic dimensions of term dependence. We also introduce a document evaluation function that allows the use of the concept hierarchy as a user profile for Information Filtering. Initial experimental results indicate that this is a promising approach for incorporating term dependence in the way documents are filtered.

A Component Based Heuristic Search Method with AdaptivePerturbations for Hospital Personnel Scheduling

Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. This paper presents a new component-based approach with adaptive perturbations, for a nurse scheduling problem arising at a major UK hospital. The main idea behind this technique is to decompose a schedule into its components (i.e. the allocated shift pattern of each nurse), and then mimic a natural evolutionary process on these components to iteratively deliver better schedules. The worthiness of all components in the schedule has to be continuously demonstrated in order for them to remain there. This demonstration employs a dynamic evaluation function which evaluates how well each component contributes towards the final objective. Two perturbation steps are then applied: the first perturbation eliminates a number of components that are deemed not worthy to stay in the current schedule; the second perturbation may also throw out, with a low level of probability, some worthy components. The eliminated components are replenished with new ones using a set of constructive heuristics using local optimality criteria. Computational results using 52 data instances demonstrate the applicability of the proposed approach in solving real-world problems.

Constraint-Informed Information Systems in Space Management Utilization

Declarative techniques such as Constraint Programming can be very effective in modeling and assisting management decisions. We present a method for managing university classrooms which extends the previous design of a Constraint-Informed Information System to generate the timetables while dealing with spatial resource optimization issues. We seek to maximize space utilization along two dimensions: classroom use and occupancy rates. While we want to maximize the room use rate, we still need to satisfy the soft constraints which model students’ and lecturers’ preferences. We present a constraint logic programming-based local search method which relies on an evaluation function that combines room utilization and timetable soft preferences. Based on this, we developed a tool which we applied to the improvement of classroom allocation in a University. Comparing the results to the current timetables obtained without optimizing space utilization, the initial versions of our tool manages to reach a 30% improvement in space utilization, while preserving the quality of the timetable, both for students and lecturers.

Flow cytometry as a tool in the evaluation of blood leukocyte function in Chelonia mydas (Linnaeus, 1758) (Testudines, Cheloniidae)

Chelonia mydas is a sea turtle that feeds and nests on the Brazilian coast and a disease called fibropapillomatosis is a threat to this species. Because of this, it is extremely necessary to determine a methodology that would enable the analysis of blood leukocyte function in these sea turtles. In order to achieve this aim, blood samples were collected from C. mydas with or without fibropapillomas captured on the São Paulo north coast. Blood samples were placed in tubes containing sodium heparin and were transported under refrigeration to the laboratory in sterile RPMI 1640 cell culture medium. Leukocytes were separated by density gradient using Ficoll-PaqueTM Plus, Amershan Biociences®. The following stimuli were applied in the assessment of leukocyte function: Phorbol Miristate-Acetate (PMA) for oxidative burst activity evaluation and Zymosan A (Saccharomyces cerevisiae) Bio Particles®, Alexa Fluor® 594 conjugate for phagocytosis evaluation. Three cell populations were identified: heterophils, monocytes and lymphocytes. Monocytes were the cells responsible for phagocytosis and oxidative burst.

Evaluation of renal function in leprosy: a study of 59 consecutive patients

Background. Renal abnormalities in leprosy have been largely described in medical literature, but there are few studies evaluating renal function in these patients. Methods. This is a cross-sectional study in 59 consecutive paucibacillary (PB) and multibacillary (MB) leprosy patients. Glomerular filtration rate (GFR) was estimated by simplified-MDRD formula. Microalbuminuria was determined by 24 h urine collection. Urinary acidification capacity was measured after water deprivation and acid-loading with CaCl2. Urinary concentration capacity was evaluated after desmopressin acetate administration, using the urinary to plasma osmolality (U/P-osm) ratio. All parameters except microalbuminuria were measured in a control group of 18 healthy volunteers. Results. Age and gender were similar between leprosy (MB or PB) and control groups. GFR <= 80 ml/min/1.73 m(2) was observed in 50% of the leprosy patients. GFR and U/P-osm in leprosy patients were significantly lower than in controls (P < 0.001). Urinary acidification defect was found in 32% of PB and in 29% of MB patients and urinary concentrating ability was abnormal in 83% of PB and 85% of MB patients. Microalbuminuria was found in 4 patients (8.5%), leukocyturia was found in 13 (22%) and haematuria was present in 16 patients (27%). Plasma creatinine (P-cr) > 1.2 mg/dl was observed in 17.9% of MB patients and in none of the controls (P = 0.020). A negative correlation was observed between GFR and time of treatment (r = -0.339; P = 0.002). Age and time of treatment were independent risk factors for GFR <= 80 ml/min/1.73 m(2) in multivariate analysis. Conclusions. Asymptomatic GFR changes and renal tubular dysfunction, including urine concentration defect and impaired acidifying mechanisms, can be caused by leprosy on specific treatment and without any reaction episodes.

Renal structure and function evaluation of rats from dams that received increased sodium intake during pregnancy and lactation submitted or not to 5/6 nephrectomy

Adult rats submitted to perinatal salt overload presented renin-angiotensin system (RAS) functional disturbances. The RAS contributes to the renal development and renal damage in a 5/6 nephrectomy model. The aim of the present study was to analyze the renal structure and function of offspring from dams that received a high-salt intake during pregnancy and lactation. We also evaluated the influence of the prenatal high-salt intake on the evolution of 5/6 nephrectomy in adult rats. A total of 111 sixty-day-old rat pups from dams that received saline or water during pregnancy and lactation were submitted to 5/6 nephrectomy (nephrectomized) or to a sham operation (sham). The animals were killed 120 days after surgery, and the kidneys were removed for immunohistochemical and histological analysis. Systolic blood pressure (SBP), albuminuria, and glomerular filtration rate (GFR) were evaluated. Increased SBP, albuminuria, and decreased GFR were observed in the rats from dams submitted to high-sodium intake before surgery. However, there was no difference in these parameters between the groups after the 5/6 nephrectomy. The scores for tubulointerstitial lesions and glomerulosclerosis were higher in the rats from the sham saline group compared to the same age control rats, but there was no difference in the histological findings between the groups of nephrectomized rats. In conclusion, our data showed that the high-salt intake during pregnancy and lactation in rats leads to structural changes in the kidney of adult offspring. However, the progression of the renal lesions after 5/6 nephrectomy was similar in both groups.

Evaluation of Sexual Function in Brazilian Pregnant Women

The objective of the present study was to evaluate the sexual function of pregnant women and to identify the potential variables associated with it. The study was conducted on 137 low-risk, sexually active pregnant women who filled out the Female Sexual Function Index (FSFI) questionnaire. Although 61% of the women assessed presented an FSFI score 26.5, they declared that they were satisfied with the emotional proximity to their partner, with their relationship, and with their sex life. A positive association was detected between sexual dysfunction and gestational age and a report of urinary incontinence and excessive weight gain in the current pregnancy.