892 resultados para Nonlinear Programming


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We study four measures of problem instance behavior that might account for the observed differences in interior-point method (IPM) iterations when these methods are used to solve semidefinite programming (SDP) problem instances: (i) an aggregate geometry measure related to the primal and dual feasible regions (aspect ratios) and norms of the optimal solutions, (ii) the (Renegar-) condition measure C(d) of the data instance, (iii) a measure of the near-absence of strict complementarity of the optimal solution, and (iv) the level of degeneracy of the optimal solution. We compute these measures for the SDPLIB suite problem instances and measure the correlation between these measures and IPM iteration counts (solved using the software SDPT3) when the measures have finite values. Our conclusions are roughly as follows: the aggregate geometry measure is highly correlated with IPM iterations (CORR = 0.896), and is a very good predictor of IPM iterations, particularly for problem instances with solutions of small norm and aspect ratio. The condition measure C(d) is also correlated with IPM iterations, but less so than the aggregate geometry measure (CORR = 0.630). The near-absence of strict complementarity is weakly correlated with IPM iterations (CORR = 0.423). The level of degeneracy of the optimal solution is essentially uncorrelated with IPM iterations.

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The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented

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This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

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These are the resources for an introductory lecture in JavaScript programming. Exercises are provided to practice simple JavaScript programming, including a template for a DHTML implementation of Conway's Game of Life (with encrypted solution).

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Exam questions and solutions for a third year mathematical programming course.

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An overview of programming and software development.

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In this lecture we describe the structure of the Programming Principles course at Southampton, look at the definitions and paradigms of programming, and take a look ahead to the key things that we will be covering in the weeks ahead.

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In this lecture we look at key concepts in Java: how to write, compile and run Java programs, define a simple class, create a main method, and use if/else structures to define behaviour.

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In this session we look more closely at the way that Java deals with variables, and in particular with the differences between primitives (basic types like int and char) and objects. We also take an initial look at the scoping rules in Java, which dictate the visibility of variables in your program

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In this session we look at how to think systematically about a problem and create a solution. We look at the definition and characteristics of an algorithm, and see how through modularisation and decomposition we can then choose a set of methods to create. We also compare this somewhat procedural approach, with the way that design works in Object Oriented Systems,

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In this session we look at how to create more powerful objects through more powerful methods. We look at parameters and call by value vs. call by reference; return types; and overloading.

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In this session we look at the public and protected keywords, and the principle of encapsulation. We also look at how Constructors can help you initialise objects, while maintaining the encapsulation principle.

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In this session we look at the different types of loop in the Java language, and see how they can be used to iterate over Arrays.

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In this session we look at how we can use collection objects like ArrayList as a more advanced type of array. We also introduce the idea of generics (forcing a collection to hold a particular type) and see how Java handles the autoboxing and unboxing of primitives. Finally we look at Iterators, a common design pattern for dealing with iteration over a collection.

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In this session we point you at the Java Library, and go into some more details on how Strings work. We also introduce the HashMap class (a very useful type of collection).