A multi-objective genetic algorithm for the design of pressure swing adsorption

Pressure Swing Adsorption (PSA) is a cyclic separation process, more advantageous over other separation options for middle scale processes. Automated tools for the design of PSA processes would be beneficial for the development of the technology, but their development is a difficult task due to the complexity of the simulation of PSA cycles and the computational effort needed to detect the performance at cyclic steady state. We present a preliminary investigation of the performance of a custom multi-objective genetic algorithm (MOGA) for the optimisation of a fast cycle PSA operation, the separation of air for N2 production. The simulation requires a detailed diffusion model, which involves coupled nonlinear partial differential and algebraic equations (PDAEs). The efficiency of MOGA to handle this complex problem has been assessed by comparison with direct search methods. An analysis of the effect of MOGA parameters on the performance is also presented

A multidirectional modified Physarum solver for discrete decision making

In this paper, a bio-inspired algorithm able to incrementally grow decision graphs in multiple directions is presented. The heuristic draws inspiration from the behaviour of the slime mould Physarum Polycephalum. In its main vegetative state, the plasmodium, this large single-celled amoeboid organism extends and optimizes a net of veins looking for food. The algorithm is here used to solve classical problems in operations research (symmetric Traveling Salesman and Vehicle Routing Problems). Simulations on selected test cases demonstrate that a multidirectional modied Physarum solver performs better than a unidirectional one. The ability to evaluate decisions from multiple directions enhances the performance of the solver in the construction and selection of optimal decision sequences

Satellite imagery fusion with an equalized trade-off between spectral and spatial quality

En este trabajo se propone una estrategia para obtener imágenes fusionadas con calidad espacial y espectral equilibradas. Esta estrategia está basada en una representación conjunta MultiDirección-MultiRresolución (MDMR), definida a partir de un banco de filtros direccional de paso bajo, complementada con una metodología de búsqueda orientada de los valores de los parámetros de diseño de este banco de filtros. La metodología de búsqueda es de carácter estocástico y optimiza una función objetivo asociada a la medida de la calidad espacial y espectral de la imagen fusionada. Los resultados obtenidos, muestran que un número pequeño de iteraciones del algoritmo de búsqueda propuesto, proporciona valores de los parámetros del banco de filtro que permiten obtener imágenes fusionadas con una calidad espectral superior a la de otros métodos investigados, manteniendo su calidad espacial

Feedback control optimisation of ESR experiments

Numerically optimised microwave pulses are used to increase excitation efficiency and modulation depth in electron spin resonance experiments performed on a spectrometer equipped with an arbitrary waveform generator. The optimisation procedure is sample-specific and reminiscent of the magnet shimming process used in the early days of nuclear magnetic resonance -- an objective function (for example, echo integral in a spin echo experiment) is defined and optimised numerically as a function of the pulse waveform vector using noise-resilient gradient-free methods. We found that the resulting shaped microwave pulses achieve higher excitation bandwidth and better echo modulation depth than the pulse shapes used as the initial guess. Although the method is theoretically less sophisticated than simulation based quantum optimal control techniques, it has the advantage of being free of the linear response approximation; rapid electron spin relaxation also means that the optimisation takes only a few seconds. This makes the procedure fast, convenient, and easy to use. An important application of this method is at the final stage of the implementation of theoretically designed pulse shapes: compensation of pulse distortions introduced by the instrument. The performance is illustrated using spin echo and out-of-phase electron spin echo envelope modulation experiments. Interface code between Bruker SpinJet arbitrary waveform generator and Matlab is included in versions 2.2 and later of the Spinach library

Alternatives with stronger convergence than coordinate-descent iterative LMI algorithms

In this note we aim at putting more emphasis on the fact that trying to solve non-convex optimization problems with coordinate-descent iterative linear matrix inequality algorithms leads to suboptimal solutions, and put forward other optimization methods better equipped to deal with such problems (having theoretical convergence guarantees and/or being more efficient in practice). This fact, already outlined at several places in the literature, still appears to be disregarded by a sizable part of the systems and control community. Thus, main elements on this issue and better optimization alternatives are presented and illustrated by means of an example.Comment: 3 pages. Main experimental results reproducible from files available on http://www.mathworks.com/matlabcentral/fileexchange/33219 This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

An Iterative Shrinkage Approach to Total-Variation Image Restoration

The problem of restoration of digital images from their degraded measurements plays a central role in a multitude of practically important applications. A particularly challenging instance of this problem occurs in the case when the degradation phenomenon is modeled by an ill-conditioned operator. In such a case, the presence of noise makes it impossible to recover a valuable approximation of the image of interest without using some a priori information about its properties. Such a priori information is essential for image restoration, rendering it stable and robust to noise. Particularly, if the original image is known to be a piecewise smooth function, one of the standard priors used in this case is defined by the Rudin-Osher-Fatemi model, which results in total variation (TV) based image restoration. The current arsenal of algorithms for TV-based image restoration is vast. In the present paper, a different approach to the solution of the problem is proposed based on the method of iterative shrinkage (aka iterated thresholding). In the proposed method, the TV-based image restoration is performed through a recursive application of two simple procedures, viz. linear filtering and soft thresholding. Therefore, the method can be identified as belonging to the group of first-order algorithms which are efficient in dealing with images of relatively large sizes. Another valuable feature of the proposed method consists in its working directly with the TV functional, rather then with its smoothed versions. Moreover, the method provides a single solution for both isotropic and anisotropic definitions of the TV functional, thereby establishing a useful connection between the two formulae.Comment: The paper was submitted to the IEEE Transactions on Image Processing on October 22nd, 200

Multidirectional Subspace Expansion for One-Parameter and Multiparameter Tikhonov Regularization

Tikhonov regularization is a popular method to approximate solutions of linear discrete ill-posed problems when the observed or measured data is contaminated by noise. Multiparameter Tikhonov regularization may improve the quality of the computed approximate solutions. We propose a new iterative method for large-scale multiparameter Tikhonov regularization with general regularization operators based on a multidirectional subspace expansion. The multidirectional subspace expansion may be combined with subspace truncation to avoid excessive growth of the search space. Furthermore, we introduce a simple and effective parameter selection strategy based on the discrepancy principle and related to perturbation results

Optimisation of composite boat hulls using first principles and design rules

The design process is becoming increasingly complex with designers balancing societal, environmental and political issues. Composite materials are attractive to designers due to excellent strength to weight ratio, low corrosion and ability to be tailored to the application. One problem with composite materials can be the low stiffness that they exhibit and as such for many applications they are stiffened. These stiffened structures create a complex engineering problem by which they must be designed to have the lowest cost and mass and yet withstand loads. This paper therefore examines the way in which rapid assessment of stiffened boat structures can be performed for the concept design stage. Navier grillage method is combined with genetic algorithms to produce panels optimised for mass and cost. These models are constrained using design rules, in this case ISO 12215 and Lloyd's Register Rules for Special Service Craft. The results show a method that produces a reasonable stiffened structure rapidly that could be used in advanced concept design or early detailed design to reduce design time