970 resultados para optimal solution


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This paper introduces a new technique for optimizing the trading strategy of brokers that autonomously trade in re- tail and wholesale markets. Simultaneous optimization of re- tail and wholesale strategies has been considered by existing studies as intractable. Therefore, each of these strategies is optimized separately and their interdependence is generally ignored, with resulting broker agents not aiming for a glob- ally optimal retail and wholesale strategy. In this paper, we propose a novel formalization, based on a semi-Markov deci- sion process (SMDP), which globally and simultaneously op- timizes retail and wholesale strategies. The SMDP is solved using hierarchical reinforcement learning (HRL) in multi- agent environments. To address the curse of dimensionality, which arises when applying SMDP and HRL to complex de- cision problems, we propose an ecient knowledge transfer approach. This enables the reuse of learned trading skills in order to speed up the learning in new markets, at the same time as making the broker transportable across market envi- ronments. The proposed SMDP-broker has been thoroughly evaluated in two well-established multi-agent simulation en- vironments within the Trading Agent Competition (TAC) community. Analysis of controlled experiments shows that this broker can outperform the top TAC-brokers. More- over, our broker is able to perform well in a wide range of environments by re-using knowledge acquired in previously experienced settings.

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In this paper, we are considered with the optimal control of a schrodinger equation. Based on the formulation for the variation of the cost functional, a gradient-type optimization technique utilizing the finite difference method is then developed to solve the constrained optimization problem. Finally, a numerical example is given and the results show that the method of solution is robust.

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AMS Subj. Classification: 49J15, 49M15

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This paper considers the global synchronisation of a stochastic version of coupled map lattices networks through an innovative stochastic adaptive linear quadratic pinning control methodology. In a stochastic network, each state receives only noisy measurement of its neighbours' states. For such networks we derive a generalised Riccati solution that quantifies and incorporates uncertainty of the forward dynamics and inverse controller in the derivation of the stochastic optimal control law. The generalised Riccati solution is derived using the Lyapunov approach. A probabilistic approximation type algorithm is employed to estimate the conditional distributions of the state and inverse controller from historical data and quantifying model uncertainties. The theoretical derivation is complemented by its validation on a set of representative examples.

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Йордан Йорданов, Андрей Василев - В работата се изследват методи за решаването на задачи на оптималното управление в дискретно време с безкраен хоризонт и явни управления. Дадена е обосновка на една процедура за решаване на такива задачи, базирана на множители на Лагранж, коята често се употребява в икономическата литература. Извеждени са необходимите условия за оптималност на базата на уравнения на Белман и са приведени достатъчни условия за оптималност при допускания, които често се използват в икономиката.

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ACM Computing Classification System (1998): G.1.1, G.1.2.

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We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where “premium” goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitated VRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW.

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We show that optimal partisan redistricting with geographical constraints is a computationally intractable (NP-complete) problem. In particular, even when voter's preferences are deterministic, a solution is generally not obtained by concentrating opponent's supporters in \unwinnable" districts ("packing") and spreading one's own supporters evenly among the other districts in order to produce many slight marginal wins ("cracking").

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Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.

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This thesis reports on 17O (I = 5/2) and 59Co (I = 7/2) quadrupole central transition (QCT) NMR studies of three classes of biologically important molecules: glucose, nicotinamide and Vitamin B12 derivatives. Extensive QCT NMR experiments were performed over a wide range of molecular motion by changing solvent viscosity and temperature. 17O-labels were introduced at the 5- and 6-positions respectively: D-[5-17O]-glucose and D-[6-17O]-glucose following the literature method. QCT NMR greatly increased the molecular size limit obtained by ordinary solution NMR. It requires much lower temperatures to get the optimal spectral resolution, which are preferable for biological molecules. In addition, quadrupolar product parameter (PQ) and shielding anisotropy product parameter (PSA) were obtained for hydroxide group and amide group for the first time. For conventional NMR studies of quadrupolar nuclei, only PQ is accessible while QCT NMR obtained both PQ and PSA simultaneously. Our experiments also suggest the resolution of QCT NMR can be even better than that obtained by conventional NMR. We observed for the first time that the second-order quadrupolar interaction becomes a dominant relaxation mechanism under ultraslow motion. All these observations suggest that QCT NMR can become a standard technique for studying quadrupolar nuclei in solution.

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Future power systems are expected to integrate large-scale stochastic and intermittent generation and load due to reduced use of fossil fuel resources, including renewable energy sources (RES) and electric vehicles (EV). Inclusion of such resources poses challenges for the dynamic stability of synchronous transmission and distribution networks, not least in terms of generation where system inertia may not be wholly governed by large-scale generation but displaced by small-scale and localised generation. Energy storage systems (ESS) can limit the impact of dispersed and distributed generation by offering supporting reserve while accommodating large-scale EV connection; the latter (load) also participating in storage provision. In this paper, a local energy storage system (LESS) is proposed. The structure, requirement and optimal sizing of the LESS are discussed. Three operating modes are detailed, including: 1) storage pack management; 2) normal operation; and 3) contingency operation. The proposed LESS scheme is evaluated using simulation studies based on data obtained from the Northern Ireland regional and residential network.

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We consider a mechanical problem concerning a 2D axisymmetric body moving forward on the plane and making slow turns of fixed magnitude about its axis of symmetry. The body moves through a medium of non-interacting particles at rest, and collisions of particles with the body's boundary are perfectly elastic (billiard-like). The body has a blunt nose: a line segment orthogonal to the symmetry axis. It is required to make small cavities with special shape on the nose so as to minimize its aerodynamic resistance. This problem of optimizing the shape of the cavities amounts to a special case of the optimal mass transfer problem on the circle with the transportation cost being the squared Euclidean distance. We find the exact solution for this problem when the amplitude of rotation is smaller than a fixed critical value, and give a numerical solution otherwise. As a by-product, we get explicit description of the solution for a class of optimal transfer problems on the circle.

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The aim of this thesis is to review and augment the theory and methods of optimal experimental design. In Chapter I the scene is set by considering the possible aims of an experimenter prior to an experiment, the statistical methods one might use to achieve those aims and how experimental design might aid this procedure. It is indicated that, given a criterion for design, a priori optimal design will only be possible in certain instances and, otherwise, some form of sequential procedure would seem to be indicated. In Chapter 2 an exact experimental design problem is formulated mathematically and is compared with its continuous analogue. Motivation is provided for the solution of this continuous problem, and the remainder of the chapter concerns this problem. A necessary and sufficient condition for optimality of a design measure is given. Problems which might arise in testing this condition are discussed, in particular with respect to possible non-differentiability of the criterion function at the design being tested. Several examples are given of optimal designs which may be found analytically and which illustrate the points discussed earlier in the chapter. In Chapter 3 numerical methods of solution of the continuous optimal design problem are reviewed. A new algorithm is presented with illustrations of how it should be used in practice. It is shown that, for reasonably large sample size, continuously optimal designs may be approximated to well by an exact design. In situations where this is not satisfactory algorithms for improvement of this design are reviewed. Chapter 4 consists of a discussion of sequentially designed experiments, with regard to both the philosophies underlying, and the application of the methods of, statistical inference. In Chapter 5 we criticise constructively previous suggestions for fully sequential design procedures. Alternative suggestions are made along with conjectures as to how these might improve performance. Chapter 6 presents a simulation study, the aim of which is to investigate the conjectures of Chapter 5. The results of this study provide empirical support for these conjectures. In Chapter 7 examples are analysed. These suggest aids to sequential experimentation by means of reduction of the dimension of the design space and the possibility of experimenting semi-sequentially. Further examples are considered which stress the importance of the use of prior information in situations of this type. Finally we consider the design of experiments when semi-sequential experimentation is mandatory because of the necessity of taking batches of observations at the same time. In Chapter 8 we look at some of the assumptions which have been made and indicate what may go wrong where these assumptions no longer hold.

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Libraries since their inception 4000 years ago have been in a process of constant change. Although, changes were in slow motion for centuries, in the last decades, academic libraries have been continuously striving to adapt their services to the ever-changing user needs of students and academic staff. In addition, e-content revolution, technological advances, and ever-shrinking budgets have obliged libraries to efficiently allocate their limited resources among collection and services. Unfortunately, this resource allocation is a complex process due to the diversity of data sources and formats required to be analyzed prior to decision-making, as well as the lack of efficient integration methods. The main purpose of this study is to develop an integrated model that supports libraries in making optimal budgeting and resource allocation decisions among their services and collection by means of a holistic analysis. To this end, a combination of several methodologies and structured approaches is conducted. Firstly, a holistic structure and the required toolset to holistically assess academic libraries are proposed to collect and organize the data from an economic point of view. A four-pronged theoretical framework is used in which the library system and collection are analyzed from the perspective of users and internal stakeholders. The first quadrant corresponds to the internal perspective of the library system that is to analyze the library performance, and costs incurred and resources consumed by library services. The second quadrant evaluates the external perspective of the library system; user’s perception about services quality is judged in this quadrant. The third quadrant analyses the external perspective of the library collection that is to evaluate the impact of the current library collection on its users. Eventually, the fourth quadrant evaluates the internal perspective of the library collection; the usage patterns followed to manipulate the library collection are analyzed. With a complete framework for data collection, these data coming from multiple sources and therefore with different formats, need to be integrated and stored in an adequate scheme for decision support. A data warehousing approach is secondly designed and implemented to integrate, process, and store the holistic-based collected data. Ultimately, strategic data stored in the data warehouse are analyzed and implemented for different purposes including the following: 1) Data visualization and reporting is proposed to allow library managers to publish library indicators in a simple and quick manner by using online reporting tools. 2) Sophisticated data analysis is recommended through the use of data mining tools; three data mining techniques are examined in this research study: regression, clustering and classification. These data mining techniques have been applied to the case study in the following manner: predicting the future investment in library development; finding clusters of users that share common interests and similar profiles, but belong to different faculties; and predicting library factors that affect student academic performance by analyzing possible correlations of library usage and academic performance. 3) Input for optimization models, early experiences of developing an optimal resource allocation model to distribute resources among the different processes of a library system are documented in this study. Specifically, the problem of allocating funds for digital collection among divisions of an academic library is addressed. An optimization model for the problem is defined with the objective of maximizing the usage of the digital collection over-all library divisions subject to a single collection budget. By proposing this holistic approach, the research study contributes to knowledge by providing an integrated solution to assist library managers to make economic decisions based on an “as realistic as possible” perspective of the library situation.

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Future power grids are envisioned to be serviced by heterogeneous arrangements of renewable energy sources. Due to their stochastic nature, energy storage distribution and management are pivotal in realizing microgrids serviced heavily by renewable energy assets. Identifying the required response characteristics to meet the operational requirements of a power grid are of great importance and must be illuminated in order to discern optimal hardware topologies. Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) presents the tools to identify such characteristics. By using energy storage as actuation within the closed loop controller, the response requirements may be identified while providing a decoupled controller solution. A DC microgrid servicing a fixed RC load through source and bus level storage managed by HSSPFC was realized in hardware. A procedure was developed to calibrate the DC microgrid architecture of this work to the reduced order model used by the HSSPFC law. Storage requirements were examined through simulation and experimental testing. Bandwidth contributions between feed forward and PI components of the HSSPFC law are illuminated and suggest the need for well-known system losses to prevent the need for additional overhead in storage allocations. The following work outlines the steps taken in realizing a DC microgrid and presents design considerations for system calibration and storage requirements per the closed loop controls for future DC microgrids.