Scheduling is a broad research area and scheduling problems arise from several application domains (production systems, logistic, computer science, etc.). Solving scheduling problems requires tools of combinatorial optimization, exact or approximated algorithms. Flexibility is at the frontier between predictive deterministic approaches and reactive or "on-line" approaches. The purpose of flexibility is to provide one or more solutions adapted to the context of the application in order to provide the ideal solution. This book focuses on the integration of flexibility and robustness considerations in the study of scheduling problems. After considering both flexibility and robustness, it then covers various scheduling problems, treated with an emphasis on flexibility or robustness, or both.

This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies. Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a “big-data'” era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.

Scheduling and multicriteria optimisation theory have been subject, separately, to numerous studies. Since the last twenty years, multicriteria scheduling problems have been subject to a growing interest. However, a gap between multicriteria scheduling approaches and multicriteria optimisation field exits. This book is an attempt to collect the elementary of multicriteria optimisation theory and the basic models and algorithms of multicriteria scheduling. It is composed of numerous illustrations, algorithms and examples which may help the reader in understanding the presented concepts. This book covers general concepts such as Pareto optimality, complexity theory, and general method for multicriteria optimisation, as well as dedicated scheduling problems and algorithms: just-in-time scheduling, flexibility and robustness, single machine problems, parallel machine problems, shop problems, etc. The second edition contains revisions and new material.

Scheduling and multicriteria optimisation theory have been subject, separately, to numerous studies. Since the last twenty years, multicriteria scheduling problems have been subject to a growing interest. However, a gap between multicriteria scheduling approaches and multicriteria optimisation field exits. This book is an attempt to collect the elementary of multicriteria optimisation theory and the basic models and algorithms of multicriteria scheduling. It is composed of numerous illustrations, algorithms and examples which may help the reader in understanding the presented concepts. This book covers general concepts such as Pareto optimality, complexity theory, and general method for multicriteria optimisation, as well as dedicated scheduling problems and algorithms: just-in-time scheduling, flexibility and robustness, single machine problems, parallel machine problems, shop problems, etc. The second edition contains revisions and new material.

A project planning and decision support model is developed and applied to identify and reduce risk and uncertainty in deconstruction project planning. It allows calculating building inventories based on sensor information and construction standards and it computes robust project plans for different scenarios with multiple modes, constrained renewable resources and locations. A reactive and flexible planning element is proposed in the case of schedule infeasibility during project execution.

The book offers an integrated vision on Cloud and HPC, Big Data, Analytics and virtualization in computing-oriented manufacturing, combining information and communication technologies, service-oriented control of holonic architectures as well as enterprise integration solutions based on SOA principles. It is structured in eight parts, each one grouping research and trends in digital manufacturing and service oriented manufacturing control: Cloud and Cyber-Physical Systems for Smart Manufacturing, Reconfigurable and Self-organized Multi-Agent Systems for Industry and Service, Sustainability Issues in Intelligent Manufacturing Systems, Holonic and Multi-agent System Design for Industry and Service, Should Intelligent Manufacturing Systems be Dependable and Safe?, Service-oriented Management and Control of Manufacturing Systems, Engineering and Human Integration in Flexible and Reconfigurable Industrial Systems,Virtualization and Simulation in Computing-oriented Industry and Service. p>

Using establishment data, we show a strong association between flexible schedules and reduced absence rates even after controlling for other family friendly policies also thought to reduce absence. The evidence suggests that the other polices, financial support for caregivers and family leave for caregivers, play a weaker role in explaining absence. The primacy of the role of schedule flexibility remains in a variety of robustness exercises including an effort to account for endogeneity. The size of the influence also shows heterogeneity as it emerges as larger in female dominated workplaces. The estimates help to inform current policy deliberations.

Evolutionary scheduling is a vital research domain at the interface of artificial intelligence and operational research. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling. It demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.

With the approach of the 21st century, and the current trends in manufacturing, the role of computer-controlled flexible manufacturing an integral part in the success of manufacturing enterprises. will take Manufacturing environments are changing to small batch (with batch sizes diminishing to a quantity of one), larger product variety, produc tion on demand with low lead times, with the ability to be 'agile.' This is in stark contrast to conventional manufacturing which has relied on economies of scale, and where change is viewed as a disruption and is therefore detrimental to production. Computer integrated manufac turing (CIM) and flexible manufacturing practices are a key component in the transition from conventional manufacturing to the 'new' manu facturing environment. While the use of computers in manufacturing, from controlling indi vidual machines (NC, Robots, AGVs etc.) to controlling flexible manu facturing systems (FMS) has advanced the flexibility of manufacturing environments, it is still far from reaching its full potential in the environment of the future. Great strides have been made in individual technologies and control of FMS has been the subject of considerable research, but computerized shop floor control is not nearly as flexible or integrated as hyped in industrial and academic literature. In fact, the integrated systems have lagged far behind what could be achieved with existing technology.