This book addresses the different problems, practices, challenges and opportunities in sustainable resource management with the help of decision-making techniques to showcase the relevance of computational modelling approaches in sustainable management and Industry 4.0. It aims to address the inherent complexity of managing ecosystems, particularly with respect to involvement of multi-stakeholders, lack of information and uncertainties. Critical analyses are made to point out the need for, and propose a call to, a new way of thinking about sustainable resource management. This book will be useful for academicians, researchers, and industrialists in the field of industrial and production engineering.

Computational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes

This collection provides a primer to the process and promise of computational modeling for industrial-organizational psychologists. With contributions by global experts in the field, the book is designed to expand readers’ appreciation for computational modeling via chapters focused on key modeling achievements in domains relevant to industrial-organizational psychology, including decision making in organizations, diversity and inclusion, learning and training, leadership, and teams. To move the use of computational modeling forward, the book includes specific how-to-chapters on two of the most commonly used modeling approaches: agent-based modeling and system dynamics modeling. It also gives guidance on how to evaluate these models qualitatively and quantitatively, and offers advice on how to read, review, and publish papers with computational models. The authors provide an extensive description of the myriad of values computational modeling can bring to the field, highlighting how they offer a more transparent, precise way to represent theories and can be simulated to offer a test of the internal consistency of a theory and allow for predictions. This is accompanied by an overview of the history of computational modeling as it relates to I-O psychology. Throughout, the authors reflect on computational modeling’s journey, looking back to its history as they imagine its future in I-O psychology. Each contribution demonstrates the value and opportunities computational modeling can provide the individual researcher, research teams, and fields of I-O psychology and management. This volume is an ideal resource for anyone interested in computational modeling, from scholarly consumers to computational model creators. Chapter 1 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

"This book contains the latest research developments in manufacturing technology and its optimization, and demonstrates the fundamentals of new computational approaches and the range of their potential application"--Provided by publisher.

The book presents select proceedings of Global meet on 'Computational Modelling and Simulation, Recent Innovations, Challenges and Perspectives, 2020. This book covers leading-edge technologies from different domains such as computation in optimization and control, multiscale and multiphysics modeling and computation analysis, environmental modeling, modeling approaches to enterprise systems and services, finite element analysis, dependability and security, high-performance computation/cloud computing applications, computational biology and chemistry and computational mechanics. The primary goal of this book is to strengthen pre-eminence in computational modeling and simulation by catalyzing the transformative use of innovative developments in a wide range of disciplines to achieve lasting societal impact. The book discusses on how to perform simulation of large complex dynamic systems in an efficient manner using advanced computational analysis. The inter-disciplinary nature of the book would be a valuable reference for academicians and research scientists, industrialists interested in modelling and simulation driven by computational technology.

The economics literature on industry dynamics contains a wide array of empirical works identifying a set of stylized facts. There have been several attempts at constructing analytical models to explain some of these regularities. These attempts are highly stylized and limited in scope to keep the analyses tractable. A general model of industry evolution capable of generating firm and industry behaviour that can match the data is needed. This book endeavours to explain many well-documented aspects of the evolution of industries over time. It uses an agent-based computational model in which artificial industries are created and grown to maturity in silico. While the firms in the model are assumed to have bounded rationality, they are nevertheless adaptive in the sense that their experience-based R&D efforts allow them to search for improved technologies. Given a technological environment subject to persistent and unexpected external shocks, the computationally generated industry remains in a perennial state of flux. The main objective of this study is to identify patterns that exist in the movements of firms as the industry evolves over time along the steady state in which the measured behaviour of the firms and the industry stochastically fluctuate around steady means. The computational model developed in this book is able to replicate many of the stylized facts from the empirical industrial organization literature, particularly as the facts pertain to the dynamics of firm entry and exit. Furthermore, the model allows examination of cross-industry variations in entry and exit patterns by systematically varying the characteristics of the market and the technological environment within which the computationally generated industry evolves. The model demonstrates that the computational approach based on boundedly rational agents in a dynamic setting can be useful and effective in carrying out both positive and normative economic analysis.

International trade is the core foundation of globalisation. This current and up-to-date volume brings together the finest academics working in the field today, containing contributions in key areas of policy research, such as, modelling frameworks, trade policy, trade and migration, trade and the environment, trade and unemployment.