Comparison of chemical clustering methods using graph- and fingerprint-based similarity measures

This paper compares several published methods for clustering chemical structures, using both graph- and fingerprint-based similarity measures. The clusterings from each method were compared to determine the degree of cluster overlap. Each method was also evaluated on how well it grouped structures into clusters possessing a non-trivial substructural commonality. The methods which employ adjustable parameters were tested to determine the stability of each parameter for datasets of varying size and composition. Our experiments suggest that both graph- and fingerprint-based similarity measures can be used effectively for generating chemical clusterings; it is also suggested that the CAST and Yin–Chen methods, suggested recently for the clustering of gene expression patterns, may also prove effective for the clustering of 2D chemical structures

A hybrid scatter search. Electromagnetism meta-heuristic for project scheduling.

In the last few decades, several effective algorithms for solving the resource-constrained project scheduling problem have been proposed. However, the challenging nature of this problem, summarised in its strongly NP-hard status, restricts the effectiveness of exact optimisation to relatively small instances. In this paper, we present a new meta-heuristic for this problem, able to provide near-optimal heuristic solutions. The procedure combines elements from scatter search, a generic population-based evolutionary search method, and a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory, hereafter referred to as the electromagnetism meta-heuristic. We present computational experiments on standard benchmark datasets, compare the results with current state-ofthe-art heuristics, and show that the procedure is capable of producing consistently good results for challenging instances of the resource-constrained project scheduling problem. We also demonstrate that the algorithm outperforms state-of-the-art existing heuristics.Algorithms; Effectiveness; Electromagnetism; Functions; Heuristic; Project scheduling; Scatter; Scatter search; Scheduling; Theory;

An Image Denoising Algorithm Based On Curvelet Transform

Aiming at the limitations of the wavelet transform in image denoising, this paper proposes a new image denoising algorithm based on curvelet transform mathematical method. In this paper, the feasibility of this method is proved by the experimental results. The experiment result shows that, using the proposed new algorithm can get high peak signal to noise ratio, visual effect is very good image

Applying the big bang-big crunch metaheuristic to large-sized operational problems

In this study, we present an investigation of comparing the capability of a big bang-big crunch metaheuristic (BBBC) for managing operational problems including combinatorial optimization problems. The BBBC is a product of the evolution theory of the universe in physics and astronomy. Two main phases of BBBC are the big bang and the big crunch. The big bang phase involves the creation of a population of random initial solutions, while in the big crunch phase these solutions are shrunk into one elite solution exhibited by a mass center. This study looks into the BBBC’s effectiveness in assignment and scheduling problems. Where it was enhanced by incorporating an elite pool of diverse and high quality solutions; a simple descent heuristic as a local search method; implicit recombination; Euclidean distance; dynamic population size; and elitism strategies. Those strategies provide a balanced search of diverse and good quality population. The investigation is conducted by comparing the proposed BBBC with similar metaheuristics. The BBBC is tested on three different classes of combinatorial optimization problems; namely, quadratic assignment, bin packing, and job shop scheduling problems. Where the incorporated strategies have a greater impact on the BBBC's performance. Experiments showed that the BBBC maintains a good balance between diversity and quality which produces high-quality solutions, and outperforms other identical metaheuristics (e.g. swarm intelligence and evolutionary algorithms) reported in the literature

Diseño óptimo de tableros isostáticos de vigas artesas prefabricadas pretensadas

Los tableros de vigas prefabricadas de hormigón pretensado se utilizan habitualmente en todo el mundo para resolver estructuras de viaductos y de pasos superiores sobre carreteras. Son escasos los trabajos de inestigación encaminados a la optimización económica de estas estructuras, donde la mayoría se han centrado en la reducción de las fuerzas de pretensado y han padecido de un signo considerablemente teórico, sin mejorar el aprovechamiento de los recursos que requieren, lo que ha dificultado su aplicación sobre los proyectos de ejecución. En la búsqueda bibliográfica, no se ha encontrado trabajo alguno enfocado a la optimización heurística económica de este tipo de estructuras. Ante el hueco existente en el espectro de la investigación, el enfoque de este trabajo está basado en la aplicación de distintas técnicas de optimización económica a esta tipología. Se han elegido técnicas metaheurísticas para poder plantear el problema lo más completo posible, donde se define todo el tablero y sus armados, y se realizan las comprobaciones que marca la normativa española. Se han analizado diferentes proyectos con esta tipología estructural, donde se han estudiado diseños de vigas artesa de distintos fabricantes, elegiendo una de ellas como modelo para realizar el presente estudio, y dejando la opción para adaptar la tipología a cualquiera de los otros diseños que se fabrican. A continuación se ha desarrollado un programa informatico en lenguage FORTRAN que incluye diferentes módulos: generación de la estructura, comprobación estructural y evaluación económica. El estudio se realiza sobre un tablero de 12 metros de ancho, con 11 de calzada, luz entre apoyos de 35 metros, y separación entre vigas de 6 metros. El estudio de los métodos heurísticos sobre el tablero, se realiza mediante la comparación de ocho distintos tipos de algoritmos: la estrategia de saltos múltiples aleatorios (RW), tres métodos de búsqueda local y cuatro de búsqueda poblacional.Martí Albiñana, JV. (2010). Diseño óptimo de tableros isostáticos de vigas artesas prefabricadas pretensadas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8640Palanci

Estudio e implementación de optimización gravitatoria y desarrollo de distintas metaheurísticas generadas a partir de él

Gran cantidad de problemas en la Ciencia y la Tecnología, como el diseño de antenas, de satélites o de sondas espaciales, por citar algunos, se plantean como problemas matemáticos en los que es necesario encontrar el mínimo de una función dependiente de un buen número de parámetros: posición, velocidad, ángulo, etc., en un determinado dominio. En nuestra tesis planteamos el estudio pormenorizado de un algoritmo, "Optimización Gravitatoria", S.G.O., diseñado para encontrar ese mínimo. Comenzamos por realizar un estudio de los fundamentos físicos y matemáticos del algoritmo para, posteriormente analizar su estructura. A continuación "ayudamos" a S.G.O. uniéndolo con otros algoritmos para potenciarlo. Dos de ello: Segmentación y Agujero de Gusano son algoritmos inéditos que han sido diseñados y desarrollados exclusivamente por nosotros. Con ellos hemos obtenido muy buenos resultados en diversas pruebas. Concluimos nuestra investigación probando los distintos algoritmos diseñados con un caso práctico: Casinni 2 que describe la trayectoria real que la homónima sonda realizó en su viaje a Saturno.In this thesis we propose the comprehensive study of the heuristic: "Space Gravitational Optimization", S.G.O., designed for global optimization of continuous functions. We study its foundations and parameters to determine their values universally. We subsequently fulfill our goal of achieving the optimum in 40 benchmark functions, common tests of effectiveness and efficiency in global optimization, with different topologies and sizes between two and thirty, several multimodal. For achieving, we join S.G.O. with algorithms of different nature: local search (Nelder-Mead and Gradient), concentration (Segmentation) and intensification (Worm Hole and Very Simple Optimization). With them metaheuristic of high effectiveness and efficiency are generated. Two of them, Segmentation and Worm Hole, are unpublished, designed and developed by us. Last but not least our work involves several tests of the different metaheuristic generated with a real instance: Cassini 2, representing the actual track made by the eponymous unmanned spacecraft on its journey to Saturn

PROFESSIONAL EMPLOYMENT

Artificial intelligence, machine learning, biologically inspired computing, cognitive science, and complex systems. Computer modeling of analogy-making. Theory and applications of evolutionary computation. Collective computation in spatially extended systems such as cellular automata, and applications to biological modeling. History of science and technology