995 resultados para scheduling sequence


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In this paper we propose a general Linear Programming (LP) based formulation and solution methodology for obtaining optimal solution to the load distribution problem in divisible load scheduling. We exploit the power of the versatile LP formulation to propose algorithms that yield exact solutions to several very general load distribution problems for which either no solutions or only heuristic solutions were available. We consider both star (single-level tree) networks and linear daisy chain networks, having processors equipped with front-ends, that form the generic models for several important network topologies. We consider arbitrary processing node availability or release times and general models for communication delays and computation time that account for constant overheads such as start up times in communication and computation. The optimality of the LP based algorithms is proved rigorously.

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The present work concerns with the static scheduling of jobs to parallel identical batch processors with incompatible job families for minimizing the total weighted tardiness. This scheduling problem is applicable in burn-in operations and wafer fabrication in semiconductor manufacturing. We decompose the problem into two stages: batch formation and batch scheduling, as in the literature. The Ant Colony Optimization (ACO) based algorithm called ATC-BACO algorithm is developed in which ACO is used to solve the batch scheduling problems. Our computational experimentation shows that the proposed ATC-BACO algorithm performs better than the available best traditional dispatching rule called ATC-BATC rule.

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The notion of optimization is inherent in protein design. A long linear chain of twenty types of amino acid residues are known to fold to a 3-D conformation that minimizes the combined inter-residue energy interactions. There are two distinct protein design problems, viz. predicting the folded structure from a given sequence of amino acid monomers (folding problem) and determining a sequence for a given folded structure (inverse folding problem). These two problems have much similarity to engineering structural analysis and structural optimization problems respectively. In the folding problem, a protein chain with a given sequence folds to a conformation, called a native state, which has a unique global minimum energy value when compared to all other unfolded conformations. This involves a search in the conformation space. This is somewhat akin to the principle of minimum potential energy that determines the deformed static equilibrium configuration of an elastic structure of given topology, shape, and size that is subjected to certain boundary conditions. In the inverse-folding problem, one has to design a sequence with some objectives (having a specific feature of the folded structure, docking with another protein, etc.) and constraints (sequence being fixed in some portion, a particular composition of amino acid types, etc.) while obtaining a sequence that would fold to the desired conformation satisfying the criteria of folding. This requires a search in the sequence space. This is similar to structural optimization in the design-variable space wherein a certain feature of structural response is optimized subject to some constraints while satisfying the governing static or dynamic equilibrium equations. Based on this similarity, in this work we apply the topology optimization methods to protein design, discuss modeling issues and present some initial results.

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Utilization bounds for Earliest Deadline First(EDF) and Rate Monotonic(RM) scheduling are known and well understood for uniprocessor systems. In this paper, we derive limits on similar bounds for the multiprocessor case, when the individual processors need not be identical. Tasks are partitioned among the processors and RM scheduling is assumed to be the policy used in individual processors. A minimum limit on the bounds for a 'greedy' class of algorithms is given and proved, since the actual value of the bound depends on the algorithm that allocates the tasks. We also derive the utilization bound of an algorithm which allocates tasks in decreasing order of utilization factors. Knowledge of such bounds allows us to carry out very fast schedulability tests although we are constrained by the fact that the tests are sufficient but not necessary to ensure schedulability.

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32P labelled 5S RNA isolated fromMycobacterium smegmatis was digested withT 1 and pancreatic ribonucleases separately and fingerprinted by two dimensional high voltage electrophoresis on thin-layer DEAE-cellulose plates. The radioactive spots were sequenced and their molar yields were determined. The chain length of the 5S RNA was found to be 120. It showed resemblances to both prokaryotic and eukaryotic 5S RNAs.

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The role of spermine in inducing A-DNA conformation in deoxyoligonucleotides has been studied using CCGG and GGCC as model sequences. It has been found that while CCGG adopts an alternating B-DNA conformation in low salt solution at low temperature, addition of spermine to this medium induces a B --greater than A transition. In contrast, the A-DNA-like structure of GGCC in low salt solution at low temperature does not change under the influence of spermine. This suggests a sequence-dependent behaviour of spermine. Further these results suggest that the A-DNA conformation observed in the crystals of d(iCCGG) and d(GGCC)2 might have been due to the presence of spermine in the crystallization cocktail.

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We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

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The sequence specific requirement for B----Z transition in solution was examined in d(CGTGCGCACG), d(CGTACGTACG), d(ACGTACGT) in presence of various Z-inducing factors. Conformational studies show that inspite of the alternating nature of purines and pyrimidines, the aforementioned sequences do not undergo B----Z transition under the influence of NaCl, hexamine cobalt chloride and ethanol. A comparison with the crystal structures of an assorted array of purine and pyrimidine sequences show that the sequence requirement for B----Z transition is much more stringent in solution as compared to the solid state. The disruptive influence of AT base pairs in B to Z transition is discussed.

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In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.

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The 3' terminal 1255 nt sequence of Physalis mottle virus (PhMV) genomic RNA has been determined from a set of overlapping cDNA clones. The open reading frame (ORF) at the 3' terminus corresponds to the amino acid sequence of the coat protein (CP) determined earlier except for the absence of the dipeptide, Lys-Leu, at position 110-111. In addiition, the sequence upstream of the CP gene contains the message coding for 178 amino acid residues of the C-terminus of the putative replicase protein (RP). The sequence downstream of the CP gene contains an untranslated region whose terminal 80 nucleotides can be folded into a characteristic tRNA-like structure. A phylogenetic tree constructed after aligning separately the sequence of the CP, the replicase protein (RP) and the tRNA-like structure determined in this study with the corresponding sequences of other tymoviruses shows that PhMV wrongly named belladonna mottle virus [BDMV(I)] is a separate tymovirus and not another strain of BDMV(E) as originally envisaged. The phylogenetic tree in all the three cases is identical showing that any subset of genomic sequence of sufficient length can be used for establishing evolutionary relationships among tymoviruses.

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Determining the sequence of amino acid residues in a heteropolymer chain of a protein with a given conformation is a discrete combinatorial problem that is not generally amenable for gradient-based continuous optimization algorithms. In this paper we present a new approach to this problem using continuous models. In this modeling, continuous "state functions" are proposed to designate the type of each residue in the chain. Such a continuous model helps define a continuous sequence space in which a chosen criterion is optimized to find the most appropriate sequence. Searching a continuous sequence space using a deterministic optimization algorithm makes it possible to find the optimal sequences with much less computation than many other approaches. The computational efficiency of this method is further improved by combining it with a graph spectral method, which explicitly takes into account the topology of the desired conformation and also helps make the combined method more robust. The continuous modeling used here appears to have additional advantages in mimicking the folding pathways and in creating the energy landscapes that help find sequences with high stability and kinetic accessibility. To illustrate the new approach, a widely used simplifying assumption is made by considering only two types of residues: hydrophobic (H) and polar (P). Self-avoiding compact lattice models are used to validate the method with known results in the literature and data that can be practically obtained by exhaustive enumeration on a desktop computer. We also present examples of sequence design for the HP models of some real proteins, which are solved in less than five minutes on a single-processor desktop computer Some open issues and future extensions are noted.

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The structure and properties of the double-helical form of the alternating copolymer poly(dA-dT) are considered. Different lines of evidence are interpreted in terms of a structure in which every second phosphate-diester linkage has a conformation different from that of the normal B form. A rationale for this “alternating-B” structure is given which provides an explanation for the effects of chemical modifications of the T residues on the binding of the poly(dA-dT)· poly(dA-dT) to the lac repressor of Escherichia coli.