Uma análise experimental de algoritmos exatos aplicados ao problema da árvore geradora multiobjetivo

The Multiobjective Spanning Tree Problem is NP-hard and models applications in several areas. This research presents an experimental analysis of different strategies used in the literature to develop exact algorithms to solve the problem. Initially, the algorithms are classified according to the approaches used to solve the problem. Features of two or more approaches can be found in some of those algorithms. The approaches investigated here are: the two-stage method, branch-and-bound, k-best and the preference-based approach. The main contribution of this research lies in the fact that no research was presented to date reporting a systematic experimental analysis of exact algorithms for the Multiobjective Spanning Tree Problem. Therefore, this work can be a basis for other research that deal with the same problem. The computational experiments compare the performance of algorithms regarding processing time, efficiency based on the number of objectives and number of solutions found in a controlled time interval. The analysis of the algorithms was performed for known instances of the problem, as well as instances obtained from a generator commonly used in the literature

Using Amino Acid Correlation and Community Detection Algorithms to Identify Functional Determinants in Protein Families

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

Use of genetic algorithms and solvation potential to study peptides structure

In this work, genetic algorithms concepts along with a rotamer library for proteins side chains and implicit solvation potential are used to optimize the tertiary structure of peptides. We starting from the known PDB structure of its backbone which is kept fixed while the side chains allowed adopting the conformations present in the rotamer library. It was used rotamer library independent of backbone and a implicit solvation potential. The structure of Mastoporan-X was predicted using several force fields with a growing complexity; we started it with a field where the only present interaction was Lennard-Jones. We added the Coulombian term and we considered the solvation effects through a term proportional to the solvent accessible area. This paper present good and interesting results obtained using the potential with solvation term and rotamer library. Hence, the algorithm (called YODA) presented here can be a good tool to the prediction problem. (c) 2007 Elsevier B.V. All rights reserved.

Combinatorial identities and quantum state densities of supersymmetric sigma models on N-folds

There is a remarkable connection between the number of quantum states of conformal theories and the sequence of dimensions of Lie algebras. In this paper, we explore this connection by computing the asymptotic expansion of the elliptic genus and the microscopic entropy of black holes associated with (supersymmetric) sigma models. The new features of these results are the appearance of correct prefactors in the state density expansion and in the coefficient of the logarithmic correction to the entropy.

Métodos de geração de colunas para problemas de atribuição

Este trabalho apresenta métodos de geração de colunas para dois importantes problemas de atribuição: o Problema Generalizado de Atribuição (PGA) e o Problema de Atribuição de Antenas a Comutadores (PAAC). O PGA é um dos mais representativos problemas de Otimização Combinatória e consiste em otimizar a atribuição de n tarefas a m agentes, de forma que cada tarefa seja atribuída a exatamente um agente e a capacidade de cada agente seja respeitada. O PAAC consiste em atribuir n antenas a m comutadores em uma rede de telefonia celular, de forma a minimizar os custos de cabeamento entre antenas e comutadores e os custos de transferência de chamadas entre comutadores. A abordagem tradicional de geração de colunas é comparada com as propostas neste trabalho, que utilizam a relaxação lagrangeana/surrogate. São apresentados testes computacionais que demonstram a efetividade dos algoritmos propostos.

Combinatorial synthesis and directed evolution applied to the production of alpha-helix forming antimicrobial peptides analogues

Antimicrobial peptides (AMPs) are effector molecules of innate immune systems found in different groups of organisms, including microorganisms, plants, insects, amphibians and humans. These peptides exhibit several structural motifs but the most abundant AMPs assume an amphipathic alpha-helical structure. The alpha-helix forming antimicrobial peptides are excellent candidates for protein engineering leading to an optimization of their biological activity and target specificity. Nowadays several approaches are available and this review deals with the use of combinatorial synthesis and directed evolution in order to provide a high-throughput source of antimicrobial peptides analogues with enhanced lytic activity and specificity.

A natural combinatorial chemistry strategy in acylpolyamine toxins from Nephilinae orb-web spiders

The present study shows how nature combined a small number of chemical building blocks to synthesize the acylpolyamine toxins in the venoms of Nephilinae orb-web spiders. Considering these structures in four parts, it was possible to rationalize a way to represent the natural combinatorial chemistry involved in the synthesis of these toxins: an aromatic moiety is connected through a linker amino acid to a polyamine chain, which in turn may be connected to an optional tail. The polyamine chains were classified into seven subtypes (from A to G) depending on the way the small chemical blocks are combined. These polyamine chains may be connected to one of the three possible chromophore moieties: 2,4-dihydroxyphenyl acetic acid, or 4-hydroxyindole acetic acid, or even with the indole acetic group. The connectivity between the aryl moiety and the polyamine chain is usually made through an asparagine residue; optionally a tail may be attached to the polyamine chain; nine different types of tails were identified among the 72 known acylpolyamine toxin structures. The combinations of three chromophores, two types of amino acid linkers, seven sub-types of polyamine backbone, and nine options of tails results in 378 different structural possibilities. However, we detected only 91 different toxin structures, which may represent the most successful structural trials in terms of efficiency of prey paralysis/death.

ACCELERATING ITERATIVE ALGORITHMS FOR SYMMETRICAL LINEAR COMPLEMENTARITY-PROBLEMS

We propose a method for accelerating iterative algorithms for solving symmetric linear complementarity problems. The method consists in performing a one-dimensional optimization in the direction generated by a splitting method even for non-descent directions. We give strong convergence proofs and present numerical experiments that justify using this acceleration.

On the dissimilarity between the algorithms for computing the symmetric energy-momentum tensor in ordinary field theory and general relativity

The recipe used to compute the symmetric energy-momentum tensor in the framework of ordinary field theory bears little resemblance to that used in the context of general relativity, if any. We show that if one stal ts fi om the field equations instead of the Lagrangian density, one obtains a unified algorithm for computing the symmetric energy-momentum tensor in the sense that it can be used for both usual field theory and general relativity.

Tabu search algorithm for network synthesis

Large scale combinatorial problems such as the network expansion problem present an amazingly high number of alternative configurations with practically the same investment, but with substantially different structures (configurations obtained with different sets of circuit/transformer additions). The proposed parallel tabu search algorithm has shown to be effective in exploring this type of optimization landscape. The algorithm is a third generation tabu search procedure with several advanced features. This is the most comprehensive combinatorial optimization technique available for treating difficult problems such as the transmission expansion planning. The method includes features of a variety of other approaches such as heuristic search, simulated annealing and genetic algorithms. In all test cases studied there are new generation, load sites which can be connected to an existing main network: such connections may require more than one line, transformer addition, which makes the problem harder in the sense that more combinations have to be considered.

Comparative studies on non-convex optimization methods for transmission network expansion planning

We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

Stochastic scheduling - A flow shop no wait application and solutions

Minimizing the makespan of a flow-shop no-wait (FSNW) schedule where the processing times are randomly distributed is an important NP-Complete Combinatorial Optimization Problem. In spite of this, it can be found only in very few papers in the literature. By considering the Start Interval Concept, this problem can be formulated, in a practical way, in function of the probability of the success in preserve FSNW constraints for all tasks execution. With this formulation, for the particular case with 3 machines, this paper presents different heuristics solutions: by integrating local optimization steps with insertion procedures and by using genetic algorithms for search the solution space. Computational results and performance evaluations are commented. Copyright (C) 1998 IFAC.

Combinatorial and geometrical properties of a class of tilings

In this paper, we consider a tiling generated by a Pisot unit number of degree d >= 3 which has a finite expansible property. We compute the states of a finite automaton which recognizes the boundary of the central tile. We also prove in the case d = 3 that the interior of each tile is simply connected.