عناصر مشابهة
Integer Programming Technique for Project Scheduling Considering Risk Management for Mega Projects
| الناشر: |
عمان
|
|---|---|
| المؤلف الرئيسي: | |
| مؤلفين آخرين: | |
| التاريخ الميلادي: | 2018 |
| الصفحات: | 1 - 88 |
| رقم MD: | 901356 |
| نوع المحتوى: | رسائل جامعية |
| اللغة: | English |
| قواعد المعلومات: | Dissertations |
| الدرجة العلمية: | رسالة ماجستير |
| الجامعة: | جامعة الاسراء الخاصة |
| الكلية: | كلية الهندسة |
| مواضيع: | |
| رابط المحتوى: |
| المستخلص: | Projects can be classified into small, medium, large and mega. This could be mainly based on several factors such number of activities, the budget of the project or the completion time. This criterions of scaling may be changed from country to another. Increase one or more of these factors, the scale of project increased. The problem of mega project scheduling that is nine out of ten mega projects have cost overrun and benefits shortfall, that are resulted from inadequate scheduling plan. This thesis develops a methodology for mega projects scheduling using heuristic approach and integer programming approach. This methodology includes three issues; time cost tradeoff, resource leveling and resource allocation. Heuristic approach uses activity on arrow network, therefore, this thesis introduces an algorithm to generate a unique activity on arrow network with minimum number of dummy activities. This developed heuristic algorithm finds the available times to complete the project and crashing cost associated to these times based on crash time for each activity and critical path calculation. A genetic algorithm is used to perform resource leveling and allocation using three indices to determine the optimum scheduling process. It also introduces integer programming model for time cost tradeoff problems using crashing time for each activity and logical relationships between activities. As a case study, a mega construction project took place in the city of Aqaba, Jordan, is used to explore the application of the proposed methodology. For this case, the proposed methodology finds the available times to complete the project. The heuristic algorithm found that the project can be completed in six different durations and each duration specify amount of crashing for each milestone individually. Furthermore, the genetic algorithm adjust scheduling of these durations based on resource limitation in order to achieve best resource improvement coefficient. The increased cost for these durations was found by integer programming model to guarantee that the increased cost is optimal. Finally, risk consideration offers to project manager to choose one of these durations based on the percentage of increased critical activities. |
|---|
