Design optimization of the APF DTL in the SSC-linac

A linear accelerator as a new injector for the SSC (Separated Sector Cyclotron) of the HIRFL (Heavy ton Research Facility Lanzhou) is being designed. The DTL (Drift-Tube-Linac) has been designed to accelerate U-238(34+) from 0.140 MeV/u to 0.97 MeV/u. To the first accelerating tank which accelerates U-238(34+) to 0.54 MeV/u, the approach of Alternating-Phase-Focusing (APF) is applied. The phase array is obtained by coupling optimization software Dakota and beam optics code LINREV. With the hybrid of Multi-objective Genetic Algorithm (MOGA) and a pattern search method, an optimum array of asynchronous phases is determined. The final growth, both transversely and longitudinally, can meet the design requirements. In this paper, the deign optimization of the APF DTL is presented.

装备维修规划的多目标优化模型和求解算法

为有效地刻画和求解军事装备系统的维修规划问题,建立了一个以维修费用和任务能力为目标的约束优化模型,提出了一种求解装备维修规划问题的多目标禁忌搜索算法。模型考虑了维修器材和工时两种费用指标,并在数质量评估的基础上通过二次回归方程来分层评估装备系统的任务能力指标。算法采用两阶段搜索策略,第一阶段从维修数量下限出发,以任务能力为演化目标进行搜索,直至找到一个可行解;第二阶段以任务能力/维修费用比为演化目标进行搜索,不断改善整个非支配解集。实验表明,算法能够求解型号≥500种,数量≥45000的大规模问题,模型和算法求解的质量也在实际应用中得到了验证。

基于神经网络的水泥生料配料多目标优化设计方法

为了降低生料成分的不确定性给水泥生料质量控制系统带来的影响,提出了率值补偿的控制策略.分别为三率值创建目标函数,并利用状态空间搜索策略解决多目标优化问题.针对初始样本空间不能覆盖所有样本的问题,提出了基于神经网络的估算模型,对初始样本空间进行拓扑.通过估价函数对状态空间中的状态量进行评价,得到最优的率值状态量;根据率值对原料配比进行调整,最后使率值偏差得到补偿,同时使给配比造成的波动最小.工业实验结果表明,生料的质量合格率由原来的30%提高到50%,该系统能有效地对配料过程进行优化控制.证明了基于神经网络的状态空间搜索策略为水泥生料配料多目标寻优问题提供了一种可行的方法。

逆向物流流量不确定闭环供应链鲁棒运作策略设计

考虑一类同时具有再分销、再制造和再利用的闭环供应链在逆向物流流量不确定环境下的运作问题.采用具有已知概率的离散情景描述逆向物流流量的不确定性,利用基于情景分析的鲁棒线性优化方法建立该闭环供应链的多目标运作模型.设计了一个数值算例,其结果验证了运作策略的鲁棒性.在该算例基础上,分析了逆向物流流量的大小对闭环供应链系统运作性能的影响.

基于遗传退火算法的装配线设计多目标优化方法

针对混装配线设计这一有约束的多目标优化问题,建立了数学模型。将基于Pareto的解的分级方法与Lp-范数形式的非线性机制相组合,构建了基于遗传退火算法多目标优化方法。重点阐述了个体编码、染色体检修、多目标处理机制等关键技术。设计了算法流程图,并开发了优化程序。该方法克服了加权和方法的不足,用模拟退火改善了遗传算法全局寻优性能。计算实例表明,随着迭代次数的增加,每代的非受控点逐渐收敛于Pareto最优边界,是一种混装线设计多目标优化的新方法。

两栖机器人轮桨腿驱动机构多目标优化设计

提出了一种既能够在陆地上爬行,又能够在一定深度的水下浮游和在海底爬行的新概念轮桨腿一体化两栖机器人;多运动模式和复合移动机构是该机器人的突出特点.分析了轮桨腿复合式驱动机构的运动机理,并采用多目标优化设计理论和算法,对驱动机构的爬行性能和浮游特性进行了综合优化,得到了两栖机器人驱动机构的结构优化参数.虚拟样机的仿真结果证明了该轮桨腿一体化两栖机器人驱动机构的综合运动性能良好,对非结构环境具有一定的适应能力。

水资源分配的决策模型及应用

水资源规划是一个复杂的系统规划问题,所以,在水资源规划中,含有大量的不精确的统计数据和模糊关系。由于这些特点,水资源规划必须用特殊的方法来解决。 本文将层次分析法(AHP)和模糊规划(Fuzzy Programming)方法相结合,形成了一种多目标规划的求解方法,并应用于大凌河流域水资源规划研究的课题中,通过实际分析可以看到,这种方法具有较好的实用性。

基于模糊多目标遗传算法的飞行器模拟件结构参数优化

空间飞行器模拟件的设计是一个具有约束的多目标多准则优化问题。本文在建立空间飞行器模拟件参数优化的数学模型的基础上,将模糊多目标决策理论用于飞行器模拟件的结构参数优化,提出了一种新的模糊评价指数。结构参数优化的结果已经用于某试验系统。

Reasoning with imprecise trade-offs in decision making under certainty and uncertainty

In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.

Optimal Scheduling Methods to Integrate Plug-In Electric Vehicles with the Power System: A Review

The introduction of the Tesla in 2008 has demonstrated to the public of the potential of electric vehicles in terms of reducing fuel consumption and green-house gas from the transport sector. It has brought electric vehicles back into the spotlight worldwide at a moment when fossil fuel prices were reaching unexpected high due to increased demand and strong economic growth. The energy storage capabilities from of fleets of electric vehicles as well as the potentially random discharging and charging offers challenges to the grid in terms of operation and control. Optimal scheduling strategies are key to integrating large numbers of electric vehicles and the smart grid. In this paper, state-of-the-art optimization methods are reviewed on scheduling strategies for the grid integration with electric vehicles. The paper starts with a concise introduction to analytical charging strategies, followed by a review of a number of classical numerical optimization methods, including linear programming, non-linear programming, dynamic programming as well as some other means such as queuing theory. Meta-heuristic techniques are then discussed to deal with the complex, high-dimensional and multi-objective scheduling problem associated with stochastic charging and discharging of electric vehicles. Finally, future research directions are suggested.

Application-Level Energy Awareness for OpenMP

Power, and consequently energy, has recently attained first-class system resource status, on par with conventional metrics such as CPU time. To reduce energy consumption, many hardware- and OS-level solutions have been investigated. However, application-level information - which can provide the system with valuable insights unattainable otherwise - was only considered in a handful of cases. We introduce OpenMPE, an extension to OpenMP designed for power management. OpenMP is the de-facto standard for programming parallel shared memory systems, but does not yet provide any support for power control. Our extension exposes (i) per-region multi-objective optimization hints and (ii) application-level adaptation parameters, in order to create energy-saving opportunities for the whole system stack. We have implemented OpenMPE support in a compiler and runtime system, and empirically evaluated its performance on two architectures, mobile and desktop. Our results demonstrate the effectiveness of OpenMPE with geometric mean energy savings across 9 use cases of 15 % while maintaining full quality of service.

Statistical Tests for Joint Analysis of Performance Measures

Recently there has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and architectural complexity). Once one has learned a model based on their devised method, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Unfortunately, the standard tests used for this purpose are not able to jointly consider performance measures. The aim of this paper is to resolve this issue by developing statistical procedures that are able to account for multiple competing measures at the same time. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameter of such models, as usually the number of studied cases is very reduced in such comparisons. Real data from a comparison among general purpose classifiers is used to show a practical application of our tests.

Location-routing problems of semi-obnoxious facilities: approaches and decision support

A presente tese resulta de um trabalho de investigação cujo objectivo se centrou no problema de localização-distribuição (PLD) que pretende abordar, de forma integrada, duas actividades logísticas intimamente relacionadas: a localização de equipamentos e a distribuição de produtos. O PLD, nomeadamente a sua modelação matemática, tem sido estudado na literatura, dando origem a diversas aproximações que resultam de diferentes cenários reais. Importa portanto agrupar as diferentes variantes por forma a facilitar e potenciar a sua investigação. Após fazer uma revisão e propor uma taxonomia dos modelos de localização-distribuição, este trabalho foca-se na resolução de alguns modelos considerados como mais representativos. É feita assim a análise de dois dos PLDs mais básicos (os problema capacitados com procura nos nós e nos arcos), sendo apresentadas, para ambos, propostas de resolução. Posteriormente, é abordada a localização-distribuição de serviços semiobnóxios. Este tipo de serviços, ainda que seja necessário e indispensável para o público em geral, dada a sua natureza, exerce um efeito desagradável sobre as comunidades contíguas. Assim, aos critérios tipicamente utilizados na tomada de decisão sobre a localização destes serviços (habitualmente a minimização de custo) é necessário adicionar preocupações que reflectem a manutenção da qualidade de vida das regiões que sofrem o impacto do resultado da referida decisão. A abordagem da localização-distribuição de serviços semiobnóxios requer portanto uma análise multi-objectivo. Esta análise pode ser feita com recurso a dois métodos distintos: não interactivos e interactivos. Ambos são abordados nesta tese, com novas propostas, sendo o método interactivo proposto aplicável a outros problemas de programação inteira mista multi-objectivo. Por último, é desenvolvida uma ferramenta de apoio à decisão para os problemas abordados nesta tese, sendo apresentada a metodologia adoptada e as suas principais funcionalidades. A ferramenta desenvolvida tem grandes preocupações com a interface de utilizador, visto ser direccionada para decisores que tipicamente não têm conhecimentos sobre os modelos matemáticos subjacentes a este tipo de problemas.

Rural engineering infrastructures design and public facility locations

O desenvolvimento das redes de estradas rurais, especialmente em áreas montanhosas, é a intervenção chave para melhorar a acessibilidade às localidades e aos serviços públicos, cobrindo o maior número de localidades e de serviços públicos, otimizando os escassos recursos disponíveis em países em desenvolvimento. Este estudo explora diferentes modelos de organização de redes de estradas rurais considerando a construção de novas ligações ou o melhoramento de estradas existentes. Um método, baseado na cobertura da rede de estradas rurais, é utilizado para identificar os pontos nodais que formam a rede rural base numa específica região, a qual cobrirá um conjunto dos serviços públicos e de localidades. O modelo assenta numa rede rural de estradas típica ("backbone" e "branch") das regiões montanhosas do Nepal. Os modelos propostos fornecem um conjunto de possibilidades de ligações a estabelecer ou a melhorar e oferece soluções para diferentes níveis de orçamento, que otimizam os custos de transporte na rede, considerando diferentes tipos de pavimento (em solo, granular ou asfáltico). Foi realizado separadamente um modelo dedicado a análises multi-objetivo para resolver problemas de melhoramento de ligações dentro da rede considerando dois objectivos, minimizar os custos de operação para o utilizador e maximizar a população coberta pela rede de estradas, considerando ligações pavimentadas e não pavimentadas (em solo, granular ou asfáltico) dentro de um determinado limite orçamental. O modelo dá ao decisor (DM) diferentes alternativas eficientes para que este possa tomar uma decisão final. Estes modelos, desenvolvidos para redes de estradas rurais, são também aplicáveis a outras redes de infraestruturas rurais, tais como, de fornecimento de água, de eletricidade e de telecomunicações. A implementação dos modelos nas redes de estradas rurais dos distritos de Gorkha e Lamjung do Nepal permitiu confirmara sua aplicabilidade. Verifica-se que os modelos propostos são mais práticos e realísticos no estudo de soluções de melhoramento e de desenvolvimento de redes de estradas rurais em regiões montanhosas de países em desenvolvimento.

Advanced optical modulation and format conversion

Over the years, the increased search and exchange of information lead to an increase of traffic intensity in todays optical communication networks. Coherent communications, using the amplitude and phase of the signal, reappears as one of the transmission techniques to increase the spectral efficiency and throughput of optical channels. In this context, this work present a study on format conversion of modulated signals using MZI-SOAs, based exclusively on all- optical techniques through wavelength conversion. This approach, when applied in interconnection nodes between optical networks with different bit rates and modulation formats, allow a better efficiency and scalability of the network. We start with an experimental characterization of the static and dynamic properties of the MZI-SOA. Then, we propose a semi-analytical model to describe the evolution of phase and amplitude at the output of the MZI-SOA. The model’s coefficients are obtained using a multi-objective genetic algorithm. We validate the model experimentally, by exploring the dependency of the optical signal with the operational parameters of the MZI-SOA. We also propose an all-optical technique for the conversion of amplitude modulation signals to a continuous phase modulation format. Finally, we study the potential of MZI-SOAs for the conversion of amplitude signals to QPSK and QAM signals. We show the dependency of the conversion process with the operational parameters deviation from the optimal values. The technique is experimentally validated for QPSK modulation.