The financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory; a network of factories in a company; or a network of companies in a supply chain. Decision Policies for Production Networks presents recent convergent research on developing policies for operating production networks including details of practical control and decision techniques which can be applied to improve the effectiveness and economic efficiency of production networks worldwide. Researchers and practitioners come together to explore a wide variety of approaches to a range of topics including: WIP and equipment management policies, Material release policies, Machine, factory, and supply chain network policies for delivery in the face of supply and demand variability, and Conflicts between complex production network models and their controlling policies. Case studies and relevant mathematical techniques are included to support and explain techniques such as heuristics, global and hierarchical optimization, control theory and filtering approaches related to complex systems or traffic flows. Decision Policies for Production Networks acts as handbook for researchers and practitioners alike, providing findings and information which can be applied to develop methods and advance further research across production networks.

The financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory; a network of factories in a company; or a network of companies in a supply chain. Decision Policies for Production Networks presents recent convergent research on developing policies for operating production networks including details of practical control and decision techniques which can be applied to improve the effectiveness and economic efficiency of production networks worldwide. Researchers and practitioners come together to explore a wide variety of approaches to a range of topics including: WIP and equipment management policies, Material release policies, Machine, factory, and supply chain network policies for delivery in the face of supply and demand variability, and Conflicts between complex production network models and their controlling policies. Case studies and relevant mathematical techniques are included to support and explain techniques such as heuristics, global and hierarchical optimization, control theory and filtering approaches related to complex systems or traffic flows. Decision Policies for Production Networks acts as handbook for researchers and practitioners alike, providing findings and information which can be applied to develop methods and advance further research across production networks.

The three volumes IFIP AICT 438, 439, and 440 constitute the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2014, held in Ajaccio, France, in September 2014. The 233 revised full papers were carefully reviewed and selected from 271 submissions. They are organized in 6 parts: knowledge discovery and sharing; knowledge-based planning and scheduling; knowledge-based sustainability; knowledge-based services; knowledge-based performance improvement, and case studies.

The phenomenon of globalization has increased in recent decades due to the opening of borders in Eastern Europe and the sudden emergence of other countries in the global trade economy. Yet, the process of becoming global to get access to growing markets or to achieve quality, service, and/or cost advantages from the reconfigured Value Chains is one

The financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory; a network of factories in a company; or a network of companies in a supply chain. Decision Policies for Production Networks presents recent convergent research on developing policies for operating production networks including details of practical control and decision techniques which can be applied to improve the effectiveness and economic efficiency of production networks worldwide. Researchers and practitioners come together to explore a wide variety of approaches to a range of topics including: WIP and equipment management policies, Material release policies, Machine, factory, and supply chain network policies for delivery in the face of supply and demand variability, and Conflicts between complex production network models and their controlling policies. Case studies and relevant mathematical techniques are included to support and explain techniques such as heuristics, global and hierarchical optimization, control theory and filtering approaches related to complex systems or traffic flows. Decision Policies for Production Networks acts as handbook for researchers and practitioners alike, providing findings and information which can be applied to develop methods and advance further research across production networks.

What are the underlying rationales for industrial policy? Does empirical evidence support the use of industrial policy for correcting market failures that plague the process of industrialization? To address these questions, the authors provide a critical survey of the analytical literature on industrial policy. They also review some recent industry successes and argue that only a limited role was played by public interventions. Moreover, the recent ascendance of international industrial networks, which dominate the sectors in which less developed countries have in the past had considerable success, implies a further limitation on the potential role of industrial policies as traditionally understood. Overall, there appears to be little empirical support for an activist government policy even though market failures exist that can, in principle, justify the use of industrial policy.

With the growing number, complexity, and importance of environmental problems come demands to include a full range of intellectual disciplines and scholarly traditions to help define and eventually manage such problems more effectively. Decision Making for the Environment: Social and Behavioral Science Research Priorities is the result of a 2-year effort by 12 social and behavioral scientists, scholars, and practitioners. The report sets research priorities for the social and behavioral sciences as they relate to several different kinds of environmental problems.

This book presents endeavors to join synergies in order to create added value for society, using the latest scientific knowledge to boost technology transfer from academia to industry. It potentiates the foundations for the creation of knowledge- and entrepreneurial cooperation networks involving engineering, innovation, and entrepreneurship stakeholders. The Regional HELIX 2018 conference was organized at the University of Minho’s School of Engineering by the MEtRICs and Algoritmi Research Centers, and took place in Guimarães, Portugal, from June 27th to 29th, 2018. After a rigorous peer-review process, 160 were accepted for publication, covering a wide range of topics, including Control, Automation and Robotics; Mechatronics Design, Medical Devices and Wellbeing; Cyber-Physical Systems, IoT and Industry 4.0; Innovations in Industrial Context and Advanced Manufacturing; New Trends in Mechanical Systems Development; Advanced Materials and Innovative Applications; Waste to Energy and Sustainable Environment; Operational Research and Industrial Mathematics; Innovation and Collaborative Arrangements; Entrepreneurship and Internationalization; and Oriented Education for Innovation, Engineering and/or Entrepreneurship.

This book presents a comprehensive overview of recent developments in production planning. The monograph begins with an introductory chapter reviewing the need for these production planning models, that operate by determining time-phased releases of work into the facility or supply chain, relating these to the Manufacturing Planning and Control (MPC) and Advanced Planning and Scheduling (APS) frameworks, that form the basis of most academic research and industrial practice. The extensive body of work on Workload Control is also placed in this context, and proves the need for improved models with a discussion of the difficulties, these approaches encounter. The next two chapters present a detailed review of the state of the art in optimization models based on exogenous planned lead times, and examines the cases where these can take both integer and fractional values. The difficulties arising in estimating planned lead times are consistent with factory behavior which are highlighted, noting that many of these lead to non-convex optimization models. Attempts to address these difficulties by iterative multimodel approaches, that combine simulation and mathematical programming, are also discussed in detail. The next three chapters of the volume address the set of techniques developed using clearing functions, which represent the expected output of a resource in a planning period, as a function of the expected workload of the resource, during that period. The chapters on this subject propose a basic optimization model for multiple products, discuss the difficulties of this model and some possible solutions. It also reviews prior work, and discuss a number of alternative formulations of the clearing function concept with their respective advantages and disadvantages. Applications to lot sizing decisions and a number of other specific problems are also described. This volume concludes with an assessment of the state of the art described in the volume, and several directions for future work.

The scope of this book is limited to heuristics, metaheuristics, and approximate methods and algorithms as applied to planning and scheduling problems. While it is not possible to give a comprehensive treatment of this topic in one book, the aim of this work is to provide the reader with a diverse set of planning and scheduling problems and different heuristic approaches to solve them. The problems range from traditional single stage and parallel machine problems to more modern settings such as robotic cells and flexible job shop networks. Furthermore, some chapters deal with deterministic problems while some others treat stochastic versions of the problems. Unlike most of the literature that deals with planning and scheduling problems in the manufacturing and production environments, in this book the environments were extended to nontraditional applications such as spatial scheduling (optimizing space over time), runway scheduling, and surgical scheduling. The solution methods used in the different chapters of the book also spread from well-established heuristics and metaheuristics such as Genetic Algorithms and Ant Colony Optimization to more recent ones such as Meta-RaPS.