30th European Symposium on Computer Aided Chemical Engineering, Volume 47 contains the papers presented at the 30th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Milan, Italy, May 24-27, 2020. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries.

This book discusses corporate citizenship, corporate responsibility and business ethics across Africa generally, and Botswana specifically. It begins by contextualizing Botswana within the broader context of Africa, using nine other countries - Angola, Cameroon, Ghana, Kenya, Nigeria, South Africa, Zambia and Zimbabwe - to provide a comparative perspective, examining the common factor: that weak legalization makes it challenging for corporate social responsibility to be actualized.From this background, the book then discusses Botswana as a key study. Botswana has been described as 'Africa's economic miracle' due to its growing economy since independence This puts it in a unique position for the implementation and study of corporate social responsibility. The interdisciplinary team of authors employ various research methods to examine the complex relationship between business, society, corporations and social justice issues.This book will be valuable reading for any academic working on corporate social responsibility in Africa, and will present an interesting insight to an often neglected area of study. France Maphosa is a Professor of Sociology at the University of Botswana. His research interests include migration and transnationalism, the sociology of entrepreneurship, corporate social responsibility, urban and rural livelihoods, labour studies and alternative dispute resolution (ADR). Langtone Maunganidze is a Senior Lecturer in the Faculty of Social Sciences at the Midlands State University in Zimbabwe. His research interests include industrial sociology, business and society, rural livelihoods and sustainable development, and entrepreneurship.

This textbook covers a diversity of topics in graph and network theory, both from a theoretical standpoint, and from an applied modelling point of view. Mathematica (R) is used to demonstrate much of the modelling aspects. Graph theory and model building tools are developed in tandem with effective techniques for solving practical problems via computer implementation. The book is designed with three primary readerships in mind. Individual syllabi or suggested sequences for study are provided for each of three student audiences: mathematics, applied mathematics/operations research, and computer science. In addition to the visual appeal of each page, the text contains an abundance of gems. Most chapters open with real-life problem descriptions which serve as motivation for the theoretical development of the subject matter. Each chapter concludes with three different sets of exercises. The first set of exercises are standard and geared toward the more mathematically inclined reader. Many of these are routine exercises, designed to test understanding of the material in the text, but some are more challenging. The second set of exercises is earmarked for the computer technologically savvy reader and offer computer exercises using Mathematica. The final set consists of larger projects aimed at equipping those readers with backgrounds in the applied sciences to apply the necessary skills learned in the chapter in the context of real-world problem solving. Additionally, each chapter offers biographical notes as well as pictures of graph theorists and mathematicians who have contributed significantly to the development of the results documented in the chapter. These notes are meant to bring the topics covered to life, allowing the reader to associate faces with some of the important discoveries and results presented. In total, approximately 100 biographical notes are presented throughout the book. The material in this book has been organized into three distinct parts, each with a different focus. The first part is devoted to topics in network optimization, with a focus on basic notions in algorithmic complexity and the computation of optimal paths, shortest spanning trees, maximum flows and minimum-cost flows in networks, as well as the solution of network location problems. The second part is devoted to a variety of classical problems in graph theory, including problems related to matchings, edge and vertex traversal, connectivity, planarity, edge and vertex coloring, and orientations of graphs. Finally, the focus in the third part is on modern areas of study in graph theory, covering graph domination, Ramsey theory, extremal graph theory, graph enumeration, and application of the probabilistic method.

This volume is the third (III) of four under the main themes of Digitizing Agriculture and Information and Communication Technologies (ICT). The four volumes cover rapidly developing processes including Sensors (I), Data (II), Decision (III), and Actions (IV). Volumes are related to 'digital transformation" within agricultural production and provision systems, and in the context of Smart Farming Technology and Knowledge-based Agriculture. Content spans broadly from data mining and visualization to big data analytics and decision making, alongside with the sustainability aspects stemming from the digital transformation of farming. The four volumes comprise the outcome of the 12th EFITA Congress, also incorporating chapters that originated from select presentations of the Congress. The focus of this book (III) is on the transformation of collected information into valuable decisions and aims to shed light on how best to use digital technologies to reduce cost, inputs, and time, toward becoming more efficient and transparent. Fourteen chapters are grouped into 3 Sections. The first section of is dedicated to decisions in the value chain of agricultural products. The next section, titled Primary Production, elaborates on decision making for the improvement of processes taking place with the farm under the implementation of ICT. The last section is devoted to the development of innovative decision applications that also consider the protection of the environment, recognizing its importance in the preservation and considerate use of resources, as well as the mitigation of adverse impacts that are related to agricultural production. Planning and modeling the assessment of agricultural practices can provide farmers with valuable information prior to the execution of any task. This book provides a valuable reference for them as well as for those directly involved with decision making in planning and assessment of agricultural production. Specific advances covered in the volume: Modelling and Simulation of ICT-based agricultural systems Farm Management Information Systems (FMIS) Planning for unmanned aerial systems Agri-robotics awareness and planning Smart livestock farming Sustainable strategic planning in agri-production Food business information systems

This book summarizes years of research in the field of fuzzy relational programming, with a special emphasis on geometric models. It discusses the state-of-the-art in fuzzy relational geometric problems, together with key open issues that must be resolved to achieve a more efficient application of this method. Though chiefly based on research conducted by the authors, who were the first to introduce fuzzy geometric problems, it also covers important findings obtained in the field of linear and non-linear programming. Thanks to its balance of basic and advanced concepts, and its wealth of practical examples, the book offers a valuable guide for both newcomers and experienced researcher in the fields of soft computing and mathematical optimization.

Understanding the concept of Entrepreneurial Orientation (EO) is of critical importance as organizations and individuals manage a world that is defined by increasing uncertainty and complexity. The need for organizations of all types and sizes to survive and thrive in such an environment demonstrates a clear need for both managers and academics to really understand EO. Building upon this foundational need to better understand EO and with both a scholarly desire to synthesize and the practical need to execute, this volume convenes some of the world's leading experts on EO to address some of the most pressing issues facing scholars and leaders in the world of practice. Within this volume, you'll discover cutting edge insights ranging from theorizing on the future of EO to an empirical investigation of its measurement. There are chapters that focus on international ventures and EO and a detailed call for a global, multidimensional view of EO. Other contributions provide contextual views of EO that examine its connections to digital work environments, family business, and more. Taken together, this volume provides readers with an overview of the current state of EO research and sets a compelling agenda for its future.

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is divided into six parts. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling. Characteristics of production environments, problem formulations, an abstract GP framework for production scheduling, and evaluation criteria are also presented. Part II shows various ways that GP can be employed to solve static production scheduling problems and their connections with conventional operation research methods. In turn, Part III shows how to design GP algorithms for dynamic production scheduling problems and describes advanced techniques for enhancing GP's performance, including feature selection, surrogate modeling, and specialized genetic operators. In Part IV, the book addresses how to use heuristics to deal with multiple, potentially conflicting objectives in production scheduling problems, and presents an advanced multi-objective approach with cooperative coevolution techniques or multi-tree representations. Part V demonstrates how to use multitask learning techniques in the hyper-heuristics space for production scheduling. It also shows how surrogate techniques and assisted task selection strategies can benefit multitask learning with GP for learning heuristics in the context of production scheduling. Part VI rounds out the text with an outlook on the future. Given its scope, the book benefits scientists, engineers, researchers, practitioners, postgraduates, and undergraduates in the areas of machine learning, artificial intelligence, evolutionary computation, operations research, and industrial engineering.

This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.

This book demonstrates that innovative ideas are systematically constructed in the creative space spanned by the dimensions of systems thinking and knowledge management. Readers will be introduced to this proposition in the final chapter, after learning about the key innovation theories, design thinking, systems thinking, and idea creation methods in systems science and knowledge science. The content provided throughout the book supports knowledge creation in various fields, the management of research and business projects, and the creation of promotion stories for products and services. Practitioners who are seeking to create innovative ideas can systematically learn the minimum theories and methods required, while graduate students will be equipped to link their research to innovation by learning the essence of systems science and knowledge science and considering selected issues. Lastly, the book includes suggestions for future research directions in knowledge science.

This book analyses decision-making in dynamic economic environments. By applying a wide range of methodological approaches, combining both analytical and computational methods, the contributors examine various aspects of optimal firm behaviour and relevant policy areas. Topics covered include optimal control, dynamic games, economic decision-making, and applications in finance and economics, as well as policy implications in areas such as pollution regulation. This book is dedicated to Christophe Deissenberg, a well-known and distinguished scholar of economic dynamics and computational economics. It appeals to academics in the areas of optimal control, dynamic games and computational economics as well as to decision-makers working in policy domains such as environmental policy.

This book has resulted from the activities of IFAC TC 5.2 "Manufacturing Modelling for Management and Control". The book offers an introduction and advanced techniques of scheduling applications to cloud manufacturing and Industry 4.0 systems for larger audience. This book uncovers fundamental principles and recent developments in the theory and application of scheduling methodology to cloud manufacturing and Industry 4.0. The purpose of this book is to present recent developments in scheduling in cloud manufacturing and Industry 4.0 and to systemize these developments in new taxonomies and methodological principles to shape this new research domain. This book addresses the needs of both researchers and practitioners to uncover the challenges and opportunities of scheduling techniques' applications to cloud manufacturing and Industry 4.0. For the first time, it comprehensively conceptualizes scheduling in cloud manufacturing and Industry 4.0 systems as a new research domain. The chapters of the book are written by the leading international experts and utilize methods of operations research, industrial engineering and computer science. Such a multi-disciplinary combination is unique and comprehensively deciphers major problem taxonomies, methodologies, and applications to scheduling in cloud manufacturing and Industry 4.0.

This book tackles the perplexing problem of how to capture the qualitative differences that exist in entrepreneurship at any given point in time or across time, by presenting a novel qualitative index: Entrepreneurship Quality Index (EQI). This comprehensive composite index is based on recognized interactions among different factors affecting intensity and types of entrepreneurial activity, which in turn is impacting the well-being. It brings qualitative differences in entrepreneurship depending on time and space into calculation of the composite index. Besides, EQI is the missing piece of the entrepreneurship puzzle, and the quality of entrepreneurship is a significant factor that shows why less developed countries do not achieve higher levels of economic growth, despite their high rate of entrepreneurial activities. This book does a masterful job in explaining the diversity of existing perspectives, their contributions, and their shortfalls. It applies rigorous tools of mathematical statistics and quality engineering, such as Bayes' rule, maximum likelihood estimation, six sigma algorithm, and standardization equation, to derive and introduce EQI, as a novel operations research model. It offers a number of important ideas and insights as to how the quality of entrepreneurship can be measured more accurately. It also illustrates the proposed approaches showing their efficacy across time. The proposed solutions are logical and empirically sound; they represent an important leap in thinking about the quality of entrepreneurship. Its contribution is crucial and timely - one that will be well recognized by researchers worldwide. They give a much-needed framework along with the necessary tools to evaluate and measure entrepreneurial activities.

This work prepares current and future managers and consultants focused on health care delivery systems to improve the efficiency of processes that deliver care. This material will help you manage capacity, improve patient flow, estimate process costs, and conduct experiments that lead to process improvement. Essential tools covered include process mapping and measurement, data collection and analysis, and the use of discrete event simulation as a tool for virtual experimentation and improvement. Tools are introduced with no assumption of prior training. Many examples of settings, problems, and solutions are presented, along with a generalized approach to process improvement that is specifically tailored to health care settings. Readings, exercises, and cases suitable for discussion or end-course projects are also provided. Writing is based on a decade of experience teaching at the MBA and MS levels, managing dozens of improvement processes, and a host of our prior scholarly publications, book chapters, and case studies.

The yard block of a container terminal is the central point of synchronisation for asynchronous container flows between deep-sea vessels and transport to the hinterland. The structure of the block stipulates that containers are stacked on top of each other with only the topmost container directly accessible by a yard crane. This book describes a holistic and integrative approach to container handling in yard blocks to optimise productivity by minimising re-handling operations. The results provide insights for academic scholars as well as for experts from practical terminal planning and operations. The approach presented is two-fold: first, a theoretical foundation of the interdependencies in decision-making is established using mathematical programming. Secondly, operations involving uncertain container arrival information are examined on the basis of a simulation with a rigorous experimental design and statistical evaluation. In this context, the book develops container-handling strategies and analyses the impact of a system for vehicle arrival management - the "Terminal Appointment System". The findings presented in this book are the result of a close cooperation with experts at the port of Hamburg and build on previous research.

This book develops innovative techniques from operational research and management science for the design and implementation of a reconfigurable manufacturing system (RMS), and subsequently analyzes and assesses their performance. A reconfigurable manufacturing system (RMS) is a paradigm that can address many of the challenges posed by the modern market. Accordingly, substantial research is now being conducted on RMS, focusing on various levels of decision-making (strategic, tactical and operational). However, as a relatively new research area, there are still only very few books and articles available on reconfigurable manufacturing system design and management. In addition to filling that gap, this book provides a forum for investigating, exchanging ideas on, and disseminating the latest advances in the broad area of RMS applications in today's industry. Gathering contributions by experts from academia, industry and policy-making, it represents an essential contribution to the existing literature on manufacturing and logistics in general and industry 4.0 in particular.

This book presents essential information on modern location science - in a word, all you need to know about location. The second edition of this handbook has been fully revised throughout, with numerous updates and chapters added, to offer an even more comprehensive overview of methods and applications. The book is divided into three parts: basic concepts, advanced concepts and applications. Written by the most respected specialists in the field and thoroughly reviewed by the editors, it first lays out the fundamental problems in location science and provides readers with basic background information on location theory. Part II covers advanced models and concepts, broadening and expanding on the content presented in Part I. It also discusses important tools to help readers grasp and solve real-world location problems. Part III focuses on the links between location science and other areas like GIS, telecommunications, healthcare, rapid transit networks, districting problems and disaster events, and presents a wide range of applications to allow readers to understand the role of facility location in such areas and learn how to handle real-world location problems. The book is intended for researchers working on theory and applications involving location problems and models. It is also suitable as a textbook for graduate courses on facility location.

This book considers a broad range of areas from decision making methods applied in the contexts of Risk, Reliability and Maintenance (RRM). Intended primarily as an update of the 2015 book Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis, this edited work provides an integration of applied probability and decision making. Within applied probability, it primarily includes decision analysis and reliability theory, amongst other topics closely related to risk analysis and maintenance. In decision making, it includes multicriteria decision making/aiding (MCDM/A) methods and optimization models. Within MCDM, in addition to decision analysis, some of the topics related to mathematical programming areas are considered, such as multiobjective linear programming, multiobjective nonlinear programming, game theory and negotiations, and multiobjective optimization. Methods related to these topics have been applied to the context of RRM. In MCDA, several other methods are considered, such as outranking methods, rough sets and constructive approaches. The book addresses an innovative treatment of decision making in RRM, improving the integration of fundamental concepts from both areas of RRM and decision making. This is accomplished by presenting current research developments in decision making on RRM. Some pitfalls of decision models on practical applications on RRM are discussed and new approaches for overcoming those drawbacks are presented.

This is a management oriented book about efficiency, quality and effectiveness designed for an audience of management practitioners, scholars, and students. The integrative approach developed in this book contains new ideas regarding quality and efficiency-based effective management. These ideas lend themselves to managerial applications. This work is not meant to provide an exhaustive account of the measurement, and applications of effectiveness, quality, and efficiency concepts. With the exception of the treatment of conventional productivity concepts and measurements in Chapter 2, and of production flexibility in Chapter 5, the discussion in this book is largely non-teclmical. Among management practitioners, the book may be of particular interest to managers with broad strategic orientations in the fields of production management, quality management, marketing, and management of human resources. The academic audience is likely to include scholars and students interested in strategic planning, applied productivity analysis, quality management, marketing management, and management of human resources. The book could also be used as a supplementary text to or part of the readings in basic and advanced courses in strategic management, production management, and quality management. Concepts and dimensions of efficiency, quality, and effectiveness, as used throughout this book, are introduced in Chapter 1. The intricate sets of relationships among effectiveness, quality, and efficiency are explored.

The Feature-Driven Method for Structural Optimization details a novel structural optimization method within a CAD framework, integrating structural optimization and feature-based design. The book presents cutting-edge research on advanced structures and introduces the feature-driven structural optimization method by regarding engineering features as basic design primitives. Consequently, it presents a method that allows structural optimization and feature design to be done simultaneously so that feature attributes are preserved throughout the design process. The book illustrates and supports the effectiveness of the method described, showing potential applications through numerical modeling techniques and programming. This volume presents a high-performance optimization method adapted to engineering structures-a novel perspective that will help engineers in the computation, modeling and design of advanced structures.

This book introduces readers to the main traffic flow modelling approaches and discusses their features and applications. It provides a comprehensive and cutting-edge review of traffic flow models, from their roots in the 1930s to the latest developments in the field. In addition, it presents problem sets that offer readers further insights into the models and hands-on experience with simulation approaches. The simulations used in the exercises can be built upon for readers' own research or other applications. The models discussed in this book are applied to describe, predict and control traffic flows on roads with the aid of rapid and accurate estimations of current and future states. The book shows how these models are developed, what their chief characteristics are, and how they can be effectively employed.

This book introduces readers to advanced data science techniques for signal mining in connection with agriculture. It shows how to apply heuristic modeling to improve farm-level efficiency, and how to use sensors and data intelligence to provide closed-loop feedback, while also providing recommendation techniques that yield actionable insights. The book also proposes certain macroeconomic pricing models, which data-mine macroeconomic signals and the influence of global economic trends on small-farm sustainability to provide actionable insights to farmers, helping them avoid financial disasters due to recurrent economic crises. The book is intended to equip current and future software engineering teams and operations research experts with the skills and tools they need in order to fully utilize advanced data science, artificial intelligence, heuristics, and economic models to develop software capabilities that help to achieve sustained food security for future generations.

The second edition of Leadership offers a unique, highly-applied academic treatise on leadership, uniquely blending a chronological analysis of the last 100 years of leadership theory with exclusive CEO interviews. The case studies, expert insights and other teaching aids are timely and hard hitting, making this textbook relevant, insightful and informative, while a research chapter empowers the reader to competently question the leaders that shape our world. The world has turned on its political and corporate axis since the first edition of Leadership was published, and it became necessary to produce a second edition that fully encapsulated, respected and observed these changes. Numerous new case studies, discussion starters and examples subsequently reflect today's volatile technological, political, financial and social shifts, while exclusive interviews with successful CEOs powerfully blend theory with practice. Readers will learn the importance of navigating leadership in the most testing of times. A new chapter, 'Researching leadership', offers the reader the opportunity to develop significantly as a leadership researcher and to ably question reality in a post-truth world. A self-leadership chapter equips the reader to develop their own leadership capabilities, while retaining the ability to avoid destructive leadership. Ultimately, readers will become empowered to appreciate the complex, intersectional nature of leadership and to learn what it takes to lead in today's politically, technologically and socially tumultuous world. This book will be particularly engaging for students and educators at secondary school, college, undergraduate and postgraduate level, and for leadership/management consultants. While the book's primary role remains as a core text for leadership, management and business modules, it will also be of interest to students on many other courses (e.g. psychology, politics, sociology). Packed with teaching resources which educators will find particularly useful, Leadership is the only textbook of its kind to offer such an applied view of this subject via the inclusion of 12 (mostly CEO) expert insights. The first edition was an "Amazon Hot New Release", so this second edition might also hold interest for a general readership.

This book offers a systematic introduction to the clustering algorithms for intuitionistic fuzzy values, the latest research results in intuitionistic fuzzy aggregation techniques, the extended results in interval-valued intuitionistic fuzzy environments, and their applications in multi-attribute decision making, such as supply chain management, military system performance evaluation, project management, venture capital, information system selection, building materials classification, and operational plan assessment, etc.

This book provides a comprehensive overview of the most important and frequently considered optimization problems concerning cutting and packing. Based on appropriate modeling approaches for the problems considered, it offers an introduction to the related solution methods. It also addresses aspects like performance results for heuristic algorithms and bounds of the optimal value, as well as the packability of a given set of objects within a predefined container. The problems discussed arise in a wide variety of different fields of application and research, and as such, the fundamental knowledge presented in this book make it a valuable resource for students, practitioners, and researchers who are interested in dealing with such tasks.

Dynamic programming (DP) has a relevant history as a powerful and flexible optimization principle, but has a bad reputation as a computationally impractical tool. This book fills a gap between the statement of DP principles and their actual software implementation. Using MATLAB throughout, this tutorial gently gets the reader acquainted with DP and its potential applications, offering the possibility of actual experimentation and hands-on experience. The book assumes basic familiarity with probability and optimization, and is suitable to both practitioners and graduate students in engineering, applied mathematics, management, finance and economics.