کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
816185 906434 2014 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Smart optimization for mega construction projects using artificial intelligence
ترجمه فارسی عنوان
بهینه سازی هوشمند برای پروژه های ساخت و ساز با استفاده از هوش مصنوعی
کلمات کلیدی
مدیریت ساخت و ساز، پروژه های ساختمانی مگا معافیت چند جانبه، الگوریتم های ژنتیک
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی (عمومی)
چکیده انگلیسی

During practicing the planning process, scheduling and controlling mega construction projects, there are varieties of procedures and methods that should be taken into consideration during project life cycle. Accordingly, it is important to consider the different modes that may be selected for an activity in the scheduling, for controlling mega construction projects. Critical Path Method “CPM” is useful for scheduling, controlling and improving mega construction projects; hence this paper presents the development of a model which incorporates the basic concepts of Critical Path Method “CPM” with a multi-objective Genetic Algorithm “GA” simultaneously. The main objective of this model is to suggest a practical support for compound horizontally and vertically mega construction planners who need to optimize resource utilization in order to minimize project duration and its cost with maximizing its quality simultaneously. Proposed software is named Smart Critical Path Method System, “SCPMS” which uses features of Critical Path Method “CPM” and multi-objective Genetic Algorithms “GAs”. The main inputs and outputs of the proposed software are demonstrated and outlined; also the main subroutines and the inference wizards are detailed. The application of this research is focused on planning and scheduling mega construction projects that hold a good promise to: (1) Increase resource use efficiency; (2) Reduce construction total time; (3) Minimize construction total cost; and (4) Measure and improve construction total quality. In addition, the verification and validation of the proposed software are tested using a real case study.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Alexandria Engineering Journal - Volume 53, Issue 3, September 2014, Pages 591–606
نویسندگان
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