Explore the vast range of titles available.

Conservation decision tools based on cost-effectiveness analysis are used to assess threat management strategies for improving species persistence. These approaches rank alternative strategies by their benefit to cost ratio but may fail to identify the optimal sets of strategies to implement under limited budgets because they do not account for redundancies. We devised a multiobjective optimization approach in which the complementarity principle is applied to identify the sets of threat management strategies that protect the most species for any budget. We used our approach to prioritize threat management strategies for 53 species of conservation concern in the Pilbara, Australia. We followed a structured elicitation approach to collect information on the benefits and costs of implementing 17 different conservation strategies during a 3-day workshop with 49 stakeholders and experts in the biodiversity, conservation, and management of the Pilbara. We compared the performance of our complementarity priority threat management approach with a current cost-effectiveness ranking approach. A complementary set of 3 strategies: domestic herbivore management, fire management and research, and sanctuaries provided all species with >50% chance of persistence for $4.7 million/year over 20 years. Achieving the same result cost almost twice as much ($9.71 million/year) when strategies were selected by their cost-effectiveness ranks alone. Our results show that complementarity of management benefits has the potential to double the impact of priority threat management approaches. Las herramientas de decisión de conservación basadas en los análisis de rentabilidad se usan para evaluar las estrategias de manejo de amenazas para mejorar la persistencia de las especies. Estos métodos clasifican a las estrategias alternativas por su beneficio al índice de costos pero pueden fallar en la identificación el conjunto óptimo de estrategias a implementar bajo un presupuesto limitado ya que no consideran las redundancias. Diseñamos una estrategia de optimización multi-objetivo en la que el principio de complementariedad es aplicado para identificar los conjuntos de estrategias de manejo de amenazas que protegen al mayor número de especies bajo cualquier presupuesto. Usamos nuestra estrategia para priorizar estrategias de manejo de amenazas para 53 especies de interés de conservación en el Pilbara, Australia. Seguimos una estrategia de obtención estructurada para colectar información sobre los costos y beneficios de implementar 17 estrategias diferentes de conservación durante un taller de tres días con 49 accionistas y expertos en biodiversidad, conservación y manejo del Pilbara. Comparamos el desempeño de nuestro método de amenazas con prioridad en lo complementario con una estrategia actual de clasificación de rentabilidad. Un conjunto complementario de tres estrategias (manejo de herbívoros domésticos, manejo de incendios e investigación, y santuarios) le proporcionó a todas las especies una oportunidad de persistencia del 50% por $4.7 millones al año durante 20 años. Obtener el mismo resultado costó casi el doble ($9.71 millones al año) cuando kas estrategias fueron seleccionadas sólo por su categoría de rentabilidad. Nuestros resultados muestran que la complementariedad de los beneficios del manejo tiene el potencial para duplicar el impacto de las estrategias de manejo de amenazas prioritarias.

In summarizing the concepts and results of the most popular fuzzy multicriteria methods, using numerical examples, this work examines all the most recently developed methods. Each one of the 22 chapters include practical applications along with new results.

The main objective of this research is to develop an optimized mixture of reactive powder concrete (RPC) containing supplementary cementitious materials (SCM), such as Electric Arc Slag Furnace (EASF), and Recycled Glass Powder (RGP) among others, through a factorial design. Accurate polynomial regressions were adjusted between considered factors and obtained responses such spread flow and compressive strength at different ages of the concrete. A multi-objective algorithm was executed to reach an eco-friendly mixture with the proper flow, the highest compressive strength, while simultaneously having the minimum content of cement. The experimental verification of this mathematical optimization demonstrated that the use of 621 kg/m3 of ASTM Type HE cement, with a maximum content of 100 kg/m3 of silica fume, should be considered the most appropriate amount to be employed in the RCP mixture to achieve a value of compressive strength over 150 MPa and a self-compacting mixture El objetivo principal de esta investigación es desarrollar una mezcla optimizada de concreto de polvos reactivos (RPC) que contenga materiales cementícios suplementarios (SCM), como la escoria siderúrgica de arco eléctrico (EASF) y el polvo de vidrio reciclado (RGP) entre otros, utilizando el diseño factorial. Se calcularon diferentes regresiones polinómicas para predecir con precisión las variables respuesta (flujo estático y resistencia a compresión a distintas edades) en función de los factores considerados. A través de un algoritmo multiobjetivo, se determinó la mezcla que alcance la resistencia y flujo estático adecuados con un contenido mínimo de cemento. La verificación experimental de esta optimización matemática mostró que con 621 kg/m3 de cemento ASTM Tipo HE, y un contenido máximo de 100 kg/m3 de humo de sílice, se puede alcanzar una resistencia a compresión superior a los 150 MPa en un concreto, además, autocompactante

With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids and flows. The presentation style is elementary enough to be accessible to anyone with exposure to basic linear algebra and graph theory, making the book suitable for introductory courses in combinatorial optimization at the upper undergraduate and beginning graduate levels. Discussions of advanced applications illustrate their potential for future application in research in approximation algorithms.

Despite spending more than any other nation on medical care per person, the United States ranks behind other industrialized nations in key health performance measures. A main cause is the deep disparities in access to care and health outcomes. Federal programs such as the designations of Medically Underserved Areas/Populations and Health Professional Shortage Areas are designed to boost the number of health professionals serving these areas and to help alleviate the access problem. Their effectiveness relies first and foremost on an accurate measure of accessibility so that resources can be allocated to truly needy areas. Various measures of accessibility need to be integrated into one framework for comparison and evaluation. Optimization methods can be used to improve the distribution and supply of health care providers to maximize service coverage, minimize travel needs of patients, limit the number of facilities, and maximize health or access equality. Inequality in health care access comes at a personal and societal price, evidenced in disparities in health outcomes, including late-stage cancer diagnosis. This review surveys recent literature on the three named issues with emphasis on methodological advancements and implications for public policy.

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models.The book presents the major machine learning methods as.

The steady-state analysis of electrical machines requires a detailed characterization of their equivalent electrical circuit, which adequately represents the transformation and interaction between electrical and mechanical energy. This research aims to characterize the equivalent circuit of three-phase induction motors by minimizing the mean square error between the measured and calculated torque variables. These torques are obtained from data provided by the manufacturer, including starting, peak, and full-load torques. A metaheuristic optimization technique is applied to solve the resulting nonlinear programming model based on the interactions between the sine and cosine functions. The numerical results obtained with this algorithm demonstrate its efficiency in terms of response quality, reaching objective function values of less than \\(110^-8\\) with regard to the measured and calculated variables. Simulation results in two test systems allow concluding that the parametric estimation problem in three-phase induction motors is a multimodal optimization problem. This implies a potentially infinite set of solutions that minimize the root mean square error and adequately represent the behavior of the motor's output torque under various probable operating conditions.

Evolutionary Topology Optimization of Continuum Structures treads new ground with a comprehensive study on the techniques and applications of evolutionary structural optimization (ESO) and its later version bi-directional ESO (BESO) methods.

La gestión de cadenas de suministro implica la formulación de modelos y metodologías para mejorar y optimizar operaciones y procesos internos, con el fin de aumentar la eficiencia, capacidad de respuesta y reducir costos. En almacenes y centros de distribución, el slotting y el picking son fundamentales para garantizar un nivel óptimo de servicio y obtener ahorros significativos en los costos logísticos. Este artículo revisa exhaustivamente los modelos y metodologías utilizados en la optimización de estas actividades entre los años 2000 y 2018, identificando aplicaciones en otras industrias, oportunidades y tendencias de investigación, considerando factores que influyen en los flujos de materiales y componentes estocásticos en la planeación de inventarios.