Techniques For Construction Network Scheduling
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Techniques for Construction Network Scheduling
This new book is for courses in construction scheduling and construction planning in departments of civil engineering, building science, engineering technology, or architecture. It provides a step-by-step approach to construction network scheduling and integrates the use of microcomputers to accomplish it. The book also contains a small case study - the Jimbeau Project - that runs throughout the text to illustrate the various network scheduling techniques that can be used on a construction project.
Network Scheduling Techniques for Construction Project Management
Author: M. Hajdu
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-09
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.
Programming and Scheduling Techniques
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.