Volume 2 begins with an introduction and 4 chapters implementing software tools on cases of practical applications and it ends with a conclusion: The various tools used in this volume Operational research with a spreadsheet Dashboards with spreadsheets and pivot tables Scheduling and planning with a project manager The traffic simulation The conclusion shows the new features that are expected to emerge on spreadsheets as well as project managers, developments and convergences between traffic simulators and new infrastructure that are emerging on road networks. Annex 1 focuses on the installation Solver in Microsoft Excel and Annex 2 focuses on the installation of the Java Development Kit.

Volume 1 presents successively an introduction followed by 10 chapters and a conclusion: A logistic approach an overview of operations research The basics of graph theory calculating optimal routes Dynamic programming planning and scheduling with PERT and MPM the waves of calculations in a network spanning trees and touring linear programming modeling of road traffic

Volume 3 begins with an introduction to which are added four chapters focused on modeling and flow simulation in an environment in 2 or 3 dimensions (2D or 3D). They deal with different cases taken from situations found in the field. A conclusion comes close this third book: The different software used in this third volume Computer simulation of discrete flows Mixed flow simulation Flows in 3D and the evacuation simulation Flows in 3D for conveying and storage The conclusion discusses the future developments of the software and their integration into society. At the end of each volume is a bibliography and a list of web links. There is also a glossary explaining some abbreviations, acronyms and some very specific terminology of logistics and operations research.

“Simulation-based Case Studies in Logistics” presents an intensive learning course on the application of simulation as a decision support tool to tackle complex logistic problems. The book describes and illustrates different approaches to developing simulation models at the right abstraction level to be used efficiently by engineers when dealing with strategic, tactical or operational decisions in logistic systems. 11 simulation-based case studies in logistics and supply chain management are discussed, based on the results of applied research, covering application areas such as production logistics, warehousing, transportation, material flow management, and hospital logistics. “Simulation-based Case Studies in Logistics” is an essential text for postgraduate engineering students and researchers working in the area of logistics modeling and simulation.

The book deals with requirements engineering in the context of System Engineering. He proposes a method to guide this activity engineering. The method is supported by the SysML modeling language. A first chapter aims to present the context and the associated definitions, to position the requirements engineering in the processes system engineering, to define the modeling and its contributions, and to make the link with the management of IS projects. The second chapter is devoted to the proposed method for implementing the requirements engineering subprocesses. Each of the 8 activities the component is first described before specifying how the SysML language can be exploited to achieve it effectively. Proposal for a book Please fill out the questionnaire below and send it back to Chantal Menascé: [email protected] The 3rd chapter is an application of the method to define the needs of the stakeholders of a system. The example is built on the basis of the RobAFIS'2018 competition. The 4th chapter continues the application of the method in the continuity of the IS processes to define the requirements of the same system. The appendices present at the same time a toolbox to realize the engineering of the requirements but also the complete results of engineering in Chapters 3 and 4.

This book covers various modern theoretical, technical, practical and technological aspects of computerized numerical control and control systems of deterministic and stochastic dynamical processes. Readers will discover: A review of the fundamentals and results of the theory of analogue control systems A clear and detailed presentation on the experimental modeling of dynamic processes Frequency synthesis techniques and in the state space of digital control systems Concrete applications of deterministic and stochastic optimal regulation laws New multimedia platforms, training and experimental automated research Various topologies and creation strategies, computer-aided telecontrol regulation systems, as well as a prototype of an automated laboratory that can be remotely operated via the Internet Simple Matlab programs to reproduce, where necessary, the main numerical and graphical results presented Many exercises corrected at the end of each chapter Detailed studies of practical automation projects, aimed at consolidating the skills of the automation profession acquired in the book

The challenges of automating socio-technical systems are strongly linked to the strengths and limitations of technical and human resources, such as perceptual characteristics, cooperative capacities, job-sharing arrangements, modeling of human behavior and the contribution of innovative design approaches. Automation Challenges of Socio-technical Systems exposes the difficulties in implementing and sustaining symbiosis between humans and machines in both the short and long terms. Furthermore, it presents innovative solutions for achieving such symbiosis, drawing on skills from cognitive sciences, engineering sciences and the social sciences. It is aimed at researchers, academics and engineers in these fields.

Although complexity makes up the very fabric of our daily lives and has been more or less addressed in a wide variety of knowledge fields, the approaches developed in the Natural Sciences and the results obtained over the past century have not yet permeated Management Sciences very much. The main features of the phenomena that the Natural Sciences deal with are: non-linear behavior, self-organization and chaos. They are analyzed with the framing of what is called “systems thinking”, popularized by the mindset pertaining to cybernetics. All pioneers in systems thinking either had direct or indirect connections with Biology, which is the discipline considered complex par excellence by the public. When applying these concepts to Operations Management Systems and modeling organizations by BDI (Beliefs, Desires, Intentions) agents, the lack of predictability in the conduct of change management that is prone to bifurcations (tipping points) in terms of organizational structures and in forecasting future activities, reveals them to be ingrained in the interplay of complexity and chaos.

The first part of the book defines the concept of uncertainties and the mathematical frameworks that will be used for uncertainty modeling. The application to system reliability assessment illustrates the concept. In the second part, evidential networks as a new tool to model uncertainty in reliability and risk analysis is proposed and described. Then it is applied on SIS performance assessment and in risk analysis of a heat sink. In the third part, Bayesian and evidential networks are used to deal with important measures evaluation in the context of uncertainties.