کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
247029 | 502400 | 2012 | 15 صفحه PDF | دانلود رایگان |

To date, few construction methods or models in the literature have discussed about helping the project managers decide the near-optimum distributions of manpower, material, equipment and space according to their project objectives and project constraints. Thus, the traditional scheduling methods or models often result in a “seat-of-the-pants” style of management, rather than decision making based on an analysis of real data. This paper presents an intelligent scheduling system (ISS) that can help the project managers to find the near-optimum schedule plan according to their project objectives and project constraints. ISS uses simulation techniques to distribute resources and assign different levels of priorities to different activities in each simulation cycle to find the near-optimal solution. ISS considers and integrates most of the important construction factors (schedule, cost, space, manpower, equipment and material) simultaneously in a unified environment, which makes the resulting schedule that will be closer to optimal. Furthermore, ISS allows for what-if analyses of possible scenarios, and schedule adjustments based on unforeseen conditions (change orders, late material delivery, etc.). Finally, two sample applications and one real-world construction project are utilized to illustrate and compare the effectiveness of ISS with two widely used software packages, Primavera Project Planner and Microsoft Project.
► Traditional scheduling methods can rarely help with decision-making based on analysis of real data.
► We developed an intelligent scheduling system (ISS) to find near-optimum schedules.
► ISS integrates schedule, cost, space, manpower, equipment and material simultaneously in a unified environment.
► ISS allows for what-if analyses of possible scenarios, and schedule adjustments for unforeseen conditions.
► ISS is compared to Primavera Project Planner and Microsoft Project.
Journal: Automation in Construction - Volume 21, January 2012, Pages 99–113