The Parameter Space Investigation (PSI) method was developed to help engineers with a wide range of multicriteria optimization problems, such as design, identification, design of control systems, and operational development of prototypes. This unique resource shows you how to use PSI to construct a feasible solution set without limitations on the number of parameters and criteria. The book presents visualization tools that are used to construct the feasible solution set, conduct multicriteria analysis, and correct the initial problem statement. You explore topics that have not been covered in any other books, including multicriteria analysis from observational data, multicriteria optimization of large-scale systems in parallel mode, adopting the PSI method for database searches, and interpretation of the prototype improvement problem. The book also offers guidance in understanding and using the accompanying, newly released MOVI software package.

Selected, peer reviewed papers from the Innovative Manufacturing Engineering Conference 2014 (IManE 2014), May 29-30, Chisinau, Republic of Moldova

With contributions from some of the top academics and scientists in the field, Advanced Studies in Multi-Criteria Decision Making presents an updated view of the landscape of Decision Sciences, current research topics, the interaction with other sciences and fields, as well as the prospects and challenges at an international level. Given that Decision Sciences are recognized today as indispensable for confronting the major societal challenges in science and technology, this book would be of interest to decision-makers, managers, and researchers from academia, and industrial/services companies that would like a fresh insight into MCDM. Features Integrates a wide range of scientific fields with a general reader approach, including applied researchers from the social, business, enterprise sciences Suitable for academics and professionals Presents a broad coverage of MCDM tools either in industry or in services companies and systems Provides a fresh overview on MCDM studies promoted by prestigious R&D institutions

Software has become ever more crucial as an enabler, from daily routines to important national decisions. But from time to time, as society adapts to frequent and rapid changes in technology, software development fails to come up to expectations due to issues with efficiency, reliability and security, and with the robustness of methodologies, tools and techniques not keeping pace with the rapidly evolving market. This book presents the proceedings of SoMeT_19, the 18th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, held in Kuching, Malaysia, from 23–25 September 2019. The book explores new trends and theories that highlight the direction and development of software methodologies, tools and techniques, and aims to capture the essence of a new state of the art in software science and its supporting technology, and to identify the challenges that such a technology will have to master. The book also investigates other comparable theories and practices in software science, including emerging technologies, from their computational foundations in terms of models, methodologies, and tools. The 56 papers included here are divided into 5 chapters: Intelligent software systems design and techniques in software engineering; Machine learning techniques for software systems; Requirements engineering, software design and development techniques; Software methodologies, tools and techniques for industry; and Knowledge science and intelligent computing. This comprehensive overview of information systems and research projects will be invaluable to all those whose work involves the assessment and solution of real-world software problems.

This book constitutes the refereed proceedings of the 13th International Conference on Computational Methods in Systems Biology, CMSB 2015, held in Nantes, France, in September 2015. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 43 full and 4 short paper submissions. The papers cover a wide range of topics in the analysis of biological systems, networks and data such as model checking, stochastic analysis, hybrid systems, circadian clock, time series data, logic programming, and constraints solving ranging from intercellular to multiscale.

Scientists and engineers use computer simulations to study relationships between a model's input parameters and its outputs. However, thorough parameter studies are challenging, if not impossible, when the simulation is expensive and the model has several inputs. To enable studies in these instances, the engineer may attempt to reduce the dimension of the model's input parameter space. Active subspaces are an emerging set of dimension reduction tools that identify important directions in the parameter space. This book describes techniques for discovering a model's active subspace and proposes methods for exploiting the reduced dimension to enable otherwise infeasible parameter studies. Readers will find new ideas for dimension reduction, easy-to-implement algorithms, and several examples of active subspaces in action.

Nonlinear Parameter Optimization Using R John C. Nash, Telfer School of Management, University of Ottawa, Canada A systematic and comprehensive treatment of optimization software using R In recent decades, optimization techniques have been streamlined by computational and artificial intelligence methods to analyze more variables, especially under non–linear, multivariable conditions, more quickly than ever before. Optimization is an important tool for decision science and for the analysis of physical systems used in engineering. Nonlinear Parameter Optimization with R explores the principal tools available in R for function minimization, optimization, and nonlinear parameter determination and features numerous examples throughout. Nonlinear Parameter Optimization with R: Provides a comprehensive treatment of optimization techniques Examines optimization problems that arise in statistics and how to solve them using R Enables researchers and practitioners to solve parameter determination problems Presents traditional methods as well as recent developments in R Is supported by an accompanying website featuring R code, examples and datasets Researchers and practitioners who have to solve parameter determination problems who are users of R but are novices in the field optimization or function minimization will benefit from this book. It will also be useful for scientists building and estimating nonlinear models in various fields such as hydrology, sports forecasting, ecology, chemical engineering, pharmaco-kinetics, agriculture, economics and statistics.

Advanced techniques of statistical inference are proposed for applications in human biology research. Major subjects concern classification and diagnosis, with special regard to the Bayesian approach. The effectiveness of such tools is tested by examples drawn from the concrete research work in the biological field. Great emphasis is placed on the use of expert systems.

As geological threats become more imminent, society must make a major commitment to increase the resilience of its communities, infrastructure, and citizens. Recent earthquakes in Japan, New Zealand, Haiti, and Chile provide stark reminders of the devastating impact major earthquakes have on the lives and economic stability of millions of people worldwide. The events in Haiti continue to show that poor planning and governance lead to long-term chaos, while nations like Chile demonstrate steady recovery due to modern earthquake planning and proper construction and mitigation activities. At the request of the National Science Foundation, the National Research Council hosted a two-day workshop to give members of the community an opportunity to identify "Grand Challenges" for earthquake engineering research that are needed to achieve an earthquake resilient society, as well as to describe networks of earthquake engineering experimental capabilities and cyberinfrastructure tools that could continue to address ongoing areas of concern. Grand Challenges in Earthquake Engineering Research: A Community Workshop Report explores the priorities and problems regions face in reducing consequent damage and spurring technological preparedness advances. Over the course of the Grand Challenges in Earthquake Engineering Research workshop, 13 grand challenge problems emerged and were summarized in terms of five overarching themes including: community resilience framework, decision making, simulation, mitigation, and design tools. Participants suggested 14 experimental facilities and cyberinfrastructure tools that would be needed to carry out testing, observations, and simulations, and to analyze the results. The report also reviews progressive steps that have been made in research and development, and considers what factors will accelerate transformative solutions.

The Special Issue on “Model-Based Tools for Pharmaceutical Manufacturing Processes” will curate novel advances in the development and application of model-based tools to address ever-present challenges of the traditional pharmaceutical manufacturing practice as well as new trends. This book provides a collection of nine papers on original advances in the model-based process unit, system-level, quality-by-design under uncertainty, and decision-making applications of pharmaceutical manufacturing processes.