Programming And Scheduling Techniques

Planning is an important management function and its effective execution is crucial to ensure the success of any project. This second edition of Thomas Uher’s and Adam Zantis' textbook maintains its focus on operational rather than strategic aspects of programming and scheduling of projects, providing the reader with the practical planning skills needed to be successful. Unlike most other textbooks that largely focus on the critical path method, Programming and Scheduling Techniques includes a comprehensive review of a range of practices used around the world. Topics covered in this thoroughly revised edition include: deterministic scheduling techniques including the bar chart, the critical path method, the critical chain method, the multiple activity chart and the line of balance a comparison of the critical path and critical chain scheduling techniques options for computer-based scheduling stochastic scheduling techniques including the critical path method based on Monte Carlo simulation and the Program Evaluation and Review Technique (PERT) risk in scheduling work study. By covering a broad range of scheduling techniques this book is suitable for those planning projects in any industry, particularly in interdisciplinary or international contexts. Written for students studying undergraduate and postgraduate architecture, building, construction/project management, quantity surveying, property development and civil engineering programs.

Brings together the most commonly used scheduling techniques in the construction industry including bar chart, critical path, multiple activity chart and line of balance. Also addresses time and resource scheduling, earned value, critical chain scheduling and probability scheduling using both Monte Carlo simulation and PERT.

Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsible for the "hardness" of the scheduling problem. Chapters 6, 7, and 8 are dedicated to the resolution of several scheduling problems. These examples illustrate the use and the practical efficiency of the constraint propagation methods of the previous chapters. They also show that besides constraint propagation, the exploration of the search space must be carefully designed, taking into account specific properties of the considered problem (e.g., dominance relations, symmetries, possible use of decomposition rules). Chapter 9 mentions various extensions of the model and presents promising research directions.

This textbook focuses on the theoretical and practical skills needed when planning and scheduling projects. As well as serving as a guide to best practice, a broad range of techniques are examined and compared to help readers understand their full range of options. Whilst this book will also prove invaluable as a reference for professionals, it has been written for students studying project management modules with planning content.

This book presents models and algorithms for complex scheduling problems. Besides resource-constrained project scheduling problems with applications also job-shop problems with flexible machines, transportation or limited buffers are discussed. Discrete optimization methods like linear and integer programming, constraint propagation techniques, shortest path and network flow algorithms, branch-and-bound methods, local search and genetic algorithms, and dynamic programming are presented. They are used in exact or heuristic procedures to solve the introduced complex scheduling problems. Furthermore, methods for calculating lower bounds are described. Most algorithms are formulated in detail and illustrated with examples. In this second edition some errors were corrected, some parts were explained in more detail, and new material has been added. In particular, further generalizations of the RCPSP, additional practical applications and some more algorithms were integrated.

Industrial, financial, commercial or any kinds of project have at least one common feature: the better organized they are, the higher the profit or the lower the cost. Project management is the principle of planning different projects and keeping them on track within time, cost and resource constraints. The need for effective project management is ever-increasing. The complexity of the environment we live in requires more sophisticated methods than it did just a couple of decades ago. Project managers might face insurmountable obstacles in their work if they do not adapt themselves to the changing circumstances. On the other hand, better knowledge of project management can result in better plans, schedules and, last but not least, more contracts and more profit. This knowledge can help individuals and firms to stay alive in this competitive market and, in the global sense, utilize the finite resources of our planet in a more efficient way.

The third edition of this well-organized and comprehensive text continues to provide an in-depth coverage of the theory and applications of operations research. It emphasizes the role of operations research not only as an effective decision-making tool, but also as an essential productivity improvement tool to deal with real-world management problems. In the growing field of analytics, this text serves to have thorough understanding of the Operations Models that form constituents of the model base, which is a component of Decision Support System. This edition includes new carefully designed numerical examples that help in understanding complex mathematical concepts better. The book is an easy read, explaining the basics of operations research and discussing various optimization techniques such as • Overview of operations research • Queuing theory • Linear programming • Project management • Transportation problem • Decision theory • Assignment problem • Game theory • Network techniques • Production scheduling • Integer programming • Goal programming • Inventory control • Parametric linear programming • Dynamic programming • Nonlinear programming NEW TO THIS EDITION • Inclusion of more mathematical models in Chapter 2. • Incorporation of case studies in all the chapters to test the understanding, analysis, and provision solution for implementation of the concerned Operation Research techniques. • Introduction of a topic on ABC analysis in Chapter 7. • Access to Multiple Choice Questions with keys for each of the chapters as online resource materials. Visit: https://www.phindia.com/Operations_research_panneerselvam This book, with numerous pedagogical features, would be eminently suitable as a text for students of engineering, B.E/B.Tech (in specific mechanical, production, and industrial engineering), mathematics, statistics, and postgraduate students of management (MBA), industrial engineering and production engineering, data analytics, commerce, and computer applications (MCA).