Multi-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problem

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Utilizando Pesos estáticos e dinâmicos em sistemas multi-classificadores com diferentes níveis de diversidade

Although some individual techniques of supervised Machine Learning (ML), also known as classifiers, or algorithms of classification, to supply solutions that, most of the time, are considered efficient, have experimental results gotten with the use of large sets of pattern and/or that they have a expressive amount of irrelevant data or incomplete characteristic, that show a decrease in the efficiency of the precision of these techniques. In other words, such techniques can t do an recognition of patterns of an efficient form in complex problems. With the intention to get better performance and efficiency of these ML techniques, were thought about the idea to using some types of LM algorithms work jointly, thus origin to the term Multi-Classifier System (MCS). The MCS s presents, as component, different of LM algorithms, called of base classifiers, and realized a combination of results gotten for these algorithms to reach the final result. So that the MCS has a better performance that the base classifiers, the results gotten for each base classifier must present an certain diversity, in other words, a difference between the results gotten for each classifier that compose the system. It can be said that it does not make signification to have MCS s whose base classifiers have identical answers to the sames patterns. Although the MCS s present better results that the individually systems, has always the search to improve the results gotten for this type of system. Aim at this improvement and a better consistency in the results, as well as a larger diversity of the classifiers of a MCS, comes being recently searched methodologies that present as characteristic the use of weights, or confidence values. These weights can describe the importance that certain classifier supplied when associating with each pattern to a determined class. These weights still are used, in associate with the exits of the classifiers, during the process of recognition (use) of the MCS s. Exist different ways of calculating these weights and can be divided in two categories: the static weights and the dynamic weights. The first category of weights is characterizes for not having the modification of its values during the classification process, different it occurs with the second category, where the values suffers modifications during the classification process. In this work an analysis will be made to verify if the use of the weights, statics as much as dynamics, they can increase the perfomance of the MCS s in comparison with the individually systems. Moreover, will be made an analysis in the diversity gotten for the MCS s, for this mode verify if it has some relation between the use of the weights in the MCS s with different levels of diversity

Algoritmo treansgenético na solução do problema do Caixeiro Viajante

The Traveling Purchaser Problem is a variant of the Traveling Salesman Problem, where there is a set of markets and a set of products. Each product is available on a subset of markets and its unit cost depends on the market where it is available. The objective is to buy all the products, departing and returning to a domicile, at the least possible cost defined as the summation of the weights of the edges in the tour and the cost paid to acquire the products. A Transgenetic Algorithm, an evolutionary algorithm with basis on endosymbiosis, is applied to the Capacited and Uncapacited versions of this problem. Evolution in Transgenetic Algorithms is simulated with the interaction and information sharing between populations of individuals from distinct species. The computational results show that this is a very effective approach for the TPP regarding solution quality and runtime. Seventeen and nine new best results are presented for instances of the capacited and uncapacited versions, respectively

O problema do caixeiro alugador com coleta de bonus: um estudo algoritmico

This paper introduces a new variant of the Traveling Car Renter Problem, named Prizecollecting Traveling Car Renter Problem. In this problem, a set of vertices, each associated with a bonus, and a set of vehicles are given. The objective is to determine a cycle that visits some vertices collecting, at least, a pre-defined bonus, and minimizing the cost of the tour that can be traveled with different vehicles. A mathematical formulation is presented and implemented in a solver to produce results for sixty-two instances. The proposed problem is also subject of an experimental study based on the algorithmic application of four metaheuristics representing the best adaptations of the state of the art of the heuristic programming.We also provide new local search operators which exploit the neighborhoods of the problem, construction procedures and adjustments, created specifically for the addressed problem. Comparative computational experiments and performance tests are performed on a sample of 80 instances, aiming to offer a competitive algorithm to the problem. We conclude that memetic algorithms, computational transgenetic and a hybrid evolutive algorithm are competitive in tests performed

Evolutionary and biogeographic history of the subfamily Neoplecostominae (Siluriformes: Loricariidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of cement thickness and bonding on the failure loads of CAD/CAM ceramic crowns: Multi-physics FEA modeling and monotonic testing

Objective. To determine the influence of cement thickness and ceramic/cement bonding on stresses and failure of CAD/CAM crowns, using both multi-physics finite element analysis and monotonic testing.Methods. Axially symmetric FEA models were created for stress analysis of a stylized monolithic crown having resin cement thicknesses from 50 to 500 mu m under occlusal loading. Ceramic-cement interface was modeled as bonded or not-bonded (cement-dentin as bonded). Cement polymerization shrinkage was simulated as a thermal contraction. Loads necessary to reach stresses for radial cracking from the intaglio surface were calculated by FEA. Experimentally, feldspathic CAD/CAM crowns based on the FEA model were machined having different occlusal cementation spaces, etched and cemented to dentin analogs. Non-bonding of etched ceramic was achieved using a thin layer of poly(dimethylsiloxane). Crowns were loaded to failure at 5 N/s, with radial cracks detected acoustically.Results. Failure loads depended on the bonding condition and the cement thickness for both FEA and physical testing. Average fracture loads for bonded crowns were: 673.5 N at 50 mu m cement and 300.6 N at 500 mu m. FEA stresses due to polymerization shrinkage increased with the cement thickness overwhelming the protective effect of bonding, as was also seen experimentally. At 50 mu m cement thickness, bonded crowns withstood at least twice the load before failure than non-bonded crowns.Significance. Occlusal "fit" can have structural implications for CAD/CAM crowns; pre-cementation spaces around 50-100 mu m being recommended from this study. Bonding benefits were lost at thickness approaching 450-500 mu m due to polymerization shrinkage stresses. (C) 2012 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Paracoccidioidomycosis: A comparative study of the evolutionary serologic, clinical and radiologic results for patients treated with ketoconazole or amphotericin B plus sulfonamides

A comparative study of two groups of patients with paracoccidioidomycosis was carried out with the objective of comparing the evolutionary serologic, clinical and radiologic results after 6, 12, 15 and 18 months of treatment with ketoconazole (22 patients) or amphotericin B plus sulfonamides (32 patients). The serologic data analyzed as a whole showed a tendency to sharper drops in antibody titers in the patients treated with ketoconazole. Clinically patients treated with ketoconazole fared better but the differences were not statistically significant. No statistical difference was detected between groups in terms of the results of radiologic evolution. © 1985 Martinus Nijhoff/Dr W. Junk Publishers.

Algorithms for network piecewise-linear programs: A comparative study

Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

Uma metodologia para o controle de seguranca dinamica de sistemas de energia eletrica

This work presents an algorithm for the security control of electric power systems using control actions like generation reallocation, determined by sensitivity analysis (linearized model) and optimization by neural networks. The model is developed taking into account the dynamic network aspects. The preventive control methodology is developed by means of sensitivity analysis of the security margin related with the mechanical power of the system synchronous machines. The reallocation power in each machine is determined using neural networks. The neural network used in this work is of Hopfield type. These networks are dedicated electric circuits which simulate the constraint set and the objective function of an optimization problem. The advantage of using these networks is the higher speed in getting the solutions when compared to conventional optimization algorithms due to the great convergence rate of the process and the facility of the method parallelization. Then, the objectives are: formulate and investigate these networks implementations in determining. The generation reallocation in digital computers. Aiming to illustrate the proposed methodology an application considering a multi-machine system is presented.

A branch-and-bound algorithm for the multi-stage transmission expansion planning

This work presents a branch-and-bound algorithm to solve the multi-stage transmission expansion planning problem. The well known transportation model is employed, nevertheless the algorithm can be extended to hybrid models or to more complex ones such as the DC model. Tests with a realistic power system were carried out in order to show the performance of the algorithm for the expansion plan executed for different time frames. © 2005 IEEE.

Distribution network reconfiguration using an efficient evolutionary algorithm

Network reconfiguration is an important tool to optimize the operating conditions of a distribution system. This is accomplished modifying the network structure of distribution feeders by changing the open/close status of sectionalizing switches. This not only reduces the power losses, but also relieves the overloading of the network components. Network reconfiguration belongs to a complex family of problems because of their combinatorial nature and multiple constraints. This paper proposes a solution to this problem, using a specialized evolutionary algorithm, with a novel codification, and a brand new way of implement the genetic operators considering the problem characteristics. The algorithm is presented and tested in a real distribution system, showing excellent results and computational efficiency. © 2007 IEEE.

Evaluating genetic algorithms with different population structures on a lot sizing and scheduling problem

This paper studies the use of different population structures in a Genetic Algorithm (GA) applied to lot sizing and scheduling problems. The population approaches are divided into two types: single-population and multi-population. The first type has a non-structured single population. The multi-population type presents non-structured and structured populations organized in binary and ternary trees. Each population approach is tested on lot sizing and scheduling problems found in soft drink companies. These problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. Computational results are reported allowing determining the better population structure for the set of problem instances evaluated. Copyright 2008 ACM.

Distribution system restoration in a DG environment using a heuristic constructive multi-start algorithm

This paper proposes a heuristic constructive multi-start algorithm (HCMA) to distribution system restoration in real time considering distributed generators installed in the system. The problem is modeled as nonlinear mixed integer and considers the two main goals of the restoration of distribution networks: minimizing the number of consumers without power and the number of switching. The proposed algorithm is implemented in C++ programming language and tested using a large real-life distribution system. The results show that the proposed algorithm is able to provide a set of feasible and good quality solutions in a suitable time for the problem. © 2011 IEEE.

GRASP with evolutionary path-relinking for the capacitated arc routing problem

The Capacitated Arc Routing Problem (CARP) is a well-known NP-hard combinatorial optimization problem where, given an undirected graph, the objective is to find a minimum cost set of tours servicing a subset of required edges under vehicle capacity constraints. There are numerous applications for the CARP, such as street sweeping, garbage collection, mail delivery, school bus routing, and meter reading. A Greedy Randomized Adaptive Search Procedure (GRASP) with Path-Relinking (PR) is proposed and compared with other successful CARP metaheuristics. Some features of this GRASP with PR are (i) reactive parameter tuning, where the parameter value is stochastically selected biased in favor of those values which historically produced the best solutions in average; (ii) a statistical filter, which discard initial solutions if they are unlikely to improve the incumbent best solution; (iii) infeasible local search, where high-quality solutions, though infeasible, are used to explore the feasible/infeasible boundaries of the solution space; (iv) evolutionary PR, a recent trend where the pool of elite solutions is progressively improved by successive relinking of pairs of elite solutions. Computational tests were conducted using a set of 81 instances, and results reveal that the GRASP is very competitive, achieving the best overall deviation from lower bounds and the highest number of best solutions found. © 2011 Elsevier Ltd. All rights reserved.

Multi-relational algorithm for mining association rules in large databases

Multi-relational data mining enables pattern mining from multiple tables. The existing multi-relational mining association rules algorithms are not able to process large volumes of data, because the amount of memory required exceeds the amount available. The proposed algorithm MRRadix presents a framework that promotes the optimization of memory usage. It also uses the concept of partitioning to handle large volumes of data. The original contribution of this proposal is enable a superior performance when compared to other related algorithms and moreover successfully concludes the task of mining association rules in large databases, bypass the problem of available memory. One of the tests showed that the MR-Radix presents fourteen times less memory usage than the GFP-growth. © 2011 IEEE.