Scheduling of a hydro producer considering head-dependency, price scenarios and risk-aversion

In this paper, a mixed-integer quadratic programming approach is proposed for the short-term hydro scheduling problem, considering head-dependency, discontinuous operating regions and discharge ramping constraints. As new contributions to earlier studies, market uncertainty is introduced in the model via price scenarios, and risk aversion is also incorporated by limiting the volatility of the expected profit through the conditional value-at-risk. Our approach has been applied successfully to solve a case Study based on one of the main Portuguese cascaded hydro systems, requiring a negligible computational time.

A random key based genetic algorithm for the resource constrained project scheduling problem

This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Avaliação de custos e avaliação de fornecedores

O presente trabalho tem como principais objetivos caracterizar os trabalhos efetuados ao longo do estágio realizado na Tramel, empresa de serralharia civil, e efetuar um estudo de avaliação de fornecedores de alumínio. O estágio desenvolveu-se essencialmente no departamento comercial e de orçamentos e no departamento de qualidade da empresa. De forma a poder desenvolver um trabalho que reunisse informação destas duas áreas foi realizado um estudo de avaliação de fornecedores de alumínio em termos de custos e de qualidade. Assim este trabalho começa por descrever o que são as serralharias, dando especial atenção aos principais materiais utilizados na empresa e tipos de tratamento usados. Depois faz uma breve referência à evolução histórica da orçamentação, distinguindo os diferentes tipos de custos e ainda à qualidade e à importância de um sistema de gestão de qualidade numa empresa. Posteriormente são referidos os trabalhos efetuados ao longo do estágio que foram previamente definidos no plano de trabalhos. Por fim é apresentado o estudo de avaliação de fornecedores de alumínio. Foram estudados os quatro principais fornecedores de alumínio da empresa e para diversos tipos de caixilhos foi determinado o custo, distinguindo no final a percentagem necessária de perfis, acessórios, tratamento, mão de obra para fabrico, lacagem e sobras. Depois é realizada uma avaliação em termos de qualidade com base em inquéritos distribuídos aos colaboradores. Finalizado o estudo realizado são tiradas conclusões e sugeridas perspetivas futuras.

Mathematical modeling and simulation of heat flow through pultrusion die assembly system for thermoset composites

Pultrusion is an industrial process used to produce glass fibers reinforced polymers profiles. These materials are worldwide used when performing characteristics, such as great electrical and magnetic insulation, high strength to weight ratio, corrosion and weather resistance, long service life and minimal maintenance are required. In this study, we present the results of the modelling and simulation of heat flow through a pultrusion die by means of Finite Element Analysis (FEA). The numerical simulation was calibrated based on temperature profiles computed from thermographic measurements carried out during pultrusion manufacturing process. Obtained results have shown a maximum deviation of 7%, which is considered to be acceptable for this type of analysis, and is below to the 10% value, previously specified as maximum deviation. © 2011, Advanced Engineering Solutions.

Lean na gestão de fluxos logísticos da Dorel Portugal, Lda.

O presente trabalho debruça-se sobre a análise de fluxos de informação e materiais na empresa Dorel Portugal, Lda.. Mais concretamente, são analisados os fluxos de transmissão de informação e os fluxos de movimentação de materiais nos duais fornecedores/armazém e armazém/setor de montagem. O estudo referido terá como propósito a identificação de elementos, associados ao estado atual, passíveis e/ou carentes de melhoria. Identificados e nomeados os pontos de intervenção, desenvolvem-se propostas de solução, as quais assentam predominantemente nos princípios e ferramentas que se associam à filosofia Lean. A escolha desta filosofia, para fundamentação de propostas, prende-se com o facto de a mesma assentar numa lógica de criação de valor pela melhoria de processo, o que espelha bem a intensão subjacente a este exercício. Foram implementadas as sugestões apresentadas e validadas junto da entidade alvo de estudo. No seguimento das implementações realizadas foi executada uma análise que permite enaltecer o ganho, seja de forma quantitativa ou qualitativa, a fim de criar impacto e sensibilizar para a importância das ações executadas. Para finalizar, importa demarcar a criação de um plano de controlo, contemplado nas ações levadas a cabo, o qual é direcionado para a manutenção do processo e concretização de medidas de melhoria contínua.

Functional domains of Bacillus subtilis transcription factor AraR and identification of aminoacids important for nucleoprotein complex assembly and effector-binding.

Journal of Bacteriology (Apr 2006) 3024-3036

Self-scheduling and bidding strategies of thermal units with stochastic emission constraints

This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Negotiation mechanism for self-organized scheduling system with collective intelligence

Current Manufacturing Systems challenges due to international economic crisis, market globalization and e-business trends, incites the development of intelligent systems to support decision making, which allows managers to concentrate on high-level tasks management while improving decision response and effectiveness towards manufacturing agility. This paper presents a novel negotiation mechanism for dynamic scheduling based on social and collective intelligence. Under the proposed negotiation mechanism, agents must interact and collaborate in order to improve the global schedule. Swarm Intelligence (SI) is considered a general aggregation term for several computational techniques, which use ideas and inspiration from the social behaviors of insects and other biological systems. This work is primarily concerned with negotiation, where multiple self-interested agents can reach agreement over the exchange of operations on competitive resources. Experimental analysis was performed in order to validate the influence of negotiation mechanism in the system performance and the SI technique. Empirical results and statistical evidence illustrate that the negotiation mechanism influence significantly the overall system performance and the effectiveness of Artificial Bee Colony for makespan minimization and on the machine occupation maximization.

Multi-agent system for distributed manufacturing scheduling with genetic algorithms and tabu search

Computerized scheduling methods and computerized scheduling systems according to exemplary embodiments. A computerized scheduling method may be stored in a memory and executed on one or more processors. The method may include defining a main multi-machine scheduling problem as a plurality of single machine scheduling problems; independently solving the plurality of single machine scheduling problems thereby calculating a plurality of near optimal single machine scheduling problem solutions; integrating the plurality of near optimal single machine scheduling problem solutions into a main multi-machine scheduling problem solution; and outputting the main multi-machine scheduling problem solution.

Saccharomyces cerevisiae Mutants Affected in Vacuole Assembly or Vacuolar H+-ATPase are Hypersensitive to Lead (Pb) Toxicity

Lead is an important environmental pollutant. The role of vacuole, in Pb detoxification, was studied using a vacuolar protein sorting mutant strain (vps16D), belonging to class C mutants. Cells disrupted in VPS16 gene, did not display a detectable vacuolar-like structure. Based on the loss of cell proliferation capacity, it was found that cells from vps16D mutant exhibited a hypersensitivity to Pb-induced toxicity, compared to wild type (WT) strain. The function of vacuolar H?-ATPase (VATPase), in Pb detoxification, was evaluated using mutants with structurally normal vacuoles but defective in subunits of catalytic (vma1D or vma2D) or membrane domain (vph1D or vma3D) of V-ATPase. All mutants tested, lacking a functional V-ATPase, displayed an increased susceptibility to Pb, comparatively to cells from WT strain. Modification of vacuolar morphology, in Pb-exposed cells, was visualized using a Vma2p-GFP strain. The treatment of yeast cells with Pb originated the fusion of the medium size vacuolar lobes into one enlarged vacuole. In conclusion, it was found that vacuole plays an important role in the detoxification of Pb in Saccharomyces cerevisiae; in addition, a functional V-ATPase was required for Pb compartmentalization.

Generalization of Wertheim's theory for the assembly of various types of rings

We generalize Wertheim's first order perturbation theory to account for the effect in the thermodynamics of the self-assembly of rings characterized by two energy scales. The theory is applied to a lattice model of patchy particles and tested against Monte Carlo simulations on a fcc lattice. These particles have 2 patches of type A and 10 patches of type B, which may form bonds AA or AB that decrease the energy by epsilon(AA) and by epsilon(AB) = r epsilon(AA), respectively. The angle theta between the 2 A-patches on each particle is fixed at 601, 90 degrees or 120 degrees. For values of r below 1/2 and above a threshold r(th)(theta) the models exhibit a phase diagram with two critical points. Both theory and simulation predict that rth increases when theta decreases. We show that the mechanism that prevents phase separation for models with decreasing values of theta is related to the formation of loops containing AB bonds. Moreover, we show that by including the free energy of B-rings ( loops containing one AB bond), the theory describes the trends observed in the simulation results, but that for the lowest values of theta, the theoretical description deteriorates due to the increasing number of loops containing more than one AB bond.

Unified overhead-aware schedulability analysis for slot-based task-splitting

Hard real- time multiprocessor scheduling has seen, in recent years, the flourishing of semi-partitioned scheduling algorithms. This category of scheduling schemes combines elements of partitioned and global scheduling for the purposes of achieving efficient utilization of the system’s processing resources with strong schedulability guarantees and with low dispatching overheads. The sub-class of slot-based “task-splitting” scheduling algorithms, in particular, offers very good trade-offs between schedulability guarantees (in the form of high utilization bounds) and the number of preemptions/migrations involved. However, so far there did not exist unified scheduling theory for such algorithms; each one was formulated in its own accompanying analysis. This article changes this fragmented landscape by formulating a more unified schedulability theory covering the two state-of-the-art slot-based semi-partitioned algorithms, S-EKG and NPS-F (both fixed job-priority based). This new theory is based on exact schedulability tests, thus also overcoming many sources of pessimism in existing analysis. In turn, since schedulability testing guides the task assignment under the schemes in consideration, we also formulate an improved task assignment procedure. As the other main contribution of this article, and as a response to the fact that many unrealistic assumptions, present in the original theory, tend to undermine the theoretical potential of such scheduling schemes, we identified and modelled into the new analysis all overheads incurred by the algorithms in consideration. The outcome is a new overhead-aware schedulability analysis that permits increased efficiency and reliability. The merits of this new theory are evaluated by an extensive set of experiments.

Dynamic cluster scheduling for cluster-tree WSNs

While Cluster-Tree network topologies look promising for WSN applications with timeliness and energy-efficiency requirements, we are yet to witness its adoption in commercial and academic solutions. One of the arguments that hinder the use of these topologies concerns the lack of flexibility in adapting to changes in the network, such as in traffic flows. This paper presents a solution to enable these networks with the ability to self-adapt their clusters’ duty-cycle and scheduling, to provide increased quality of service to multiple traffic flows. Importantly, our approach enables a network to change its cluster scheduling without requiring long inaccessibility times or the re-association of the nodes. We show how to apply our methodology to the case of IEEE 802.15.4/ZigBee cluster-tree WSNs without significant changes to the protocol. Finally, we analyze and demonstrate the validity of our methodology through a comprehensive simulation and experimental validation using commercially available technology on a Structural Health Monitoring application scenario.